Santa Fe Institute Events Wiki - User contributions [en]

CSSS 2008 Santa Fe-Final Papers

2008-08-18T21:43:21Z

Drown:

{{CSSS 2008 Santa Fe}}



[[media: Learning.pdf | Learning the Basics of Learning]] by Béla Nagy, David Papo, and Tihamér von Ghyczy.

[[media: Segregation.pdf | Spatial Patterns of Segregation: A generative model]] by Flávia Feitosa, Joshua Reyes, and Walter Zesk

[http://www.santafe.edu/events/workshops/images/f/fc/CSSS_2008_Project_Org_Adapt_Final.pdf Exploring a Model of Organizational Adaptability] by Shawn Barr, Steve Hall, W. Brad Jones, Catherine Spence, Richard Streeter, and Jiang Wu

[[media: HP Modularity Drown Rorick Mills Moffett.pdf | Modularity in coevolving host-pathogen systems]] by Devin Drown, Molly Rorick, Rob Mills and Alex Moffett

File:HP Modularity Drown Rorick Mills Moffett.pdf

2008-08-18T21:40:30Z

Drown:

HP Modularity

2008-06-25T04:37:52Z

Drown: /* Host-Pathogen Modularity */

== Host-Pathogen Modularity ==

This is the working space for our project. Everything written is a work in progress.

=== Working Draft of Paper ===

Below is the current link to the working draft of the paper. I'm not sure if this will really work for version control. Perhaps people can just send me sections and I'll incorporate as needed. -Devin

'''NOT CHECKED OUT'''

[http://www.santafe.edu/events/workshops/images/e/e6/Hp_modularity_v1.doc Link to Word Doc]

[http://www.santafe.edu/events/workshops/index.php/Image:Hp_modularity_v1.doc Link to upload]

=== Title Ideas ===
*'''Modularity in coevolving host-pathogen systems'''
*Evolution of modularity in a host-pathogen system
*Modularity: a pathogen's answer to host interactions
* Do host-pathogen interactions lead to the adaptive evolution for modularity?
*more here

=== Perspectives on Modularity and Evolvability from the Literature ===

This section might help to structure our understanding of the general consensus regarding the evolution of modularity. It seems that there are a rather large number of individuals that are skeptical regarding the selective advantages of modularity (Lynch 2007), though it does not appear that any of these individuals have considered the role that host-pathogens may play in determining the benefits associated with modularity, and so we might attempt to motivate our study on this basis.

#"There is no evidence that the modular structure of gene regulatory regions or genetic networks is directly advanced by selective mechanisms. However, the processes of duplication, degenerative mutation, and random genetic drift can lead to the passive emergence of modularity in populations of with genetic effective sizes of the magnitude found in multicellular species" (Lynch 2007, p. 8598).
#Four reasons to question the selective origins of modularity: (i) evolvability is a feature of a population and is thus the focus of group selection, which is less strong than selection acting at the level of the individual; (ii) "[i]t is by no means clear that an enhanced ability to evolve is generally advantageous"; (iii) "there is no evidence that phylogenetic variation in evolutionary features reflects anything more than diversity in variation generating factors that exist for purely physical reasons"; and (iv) "comparative genomics provides no support for the idea that genome architectural changes have been promoted in multicellular lineages so as to enhance their ability to evolve" (Lynch 2007, p. 8603).
#Orr (2000) and Welch and Waxman (2003) have used Fisher's geometric model to study the evolutionary cost of complexity. Both studies concluded, perhaps surprisingly, that this cost is quite high.

=== ''Major'' Questions ===
#Does modularity in pathogen ''genes'' responsible for an interaction with a host increase its ability to adapt to a host?
#under what conditions does pathogen modularity arise? specifically,
## Is modularity in the host required?
## what configurations of the interaction matrix?
## what influence does population structure have (in the hosts)?
#additional ones here

=== Questions to answer in proposal ===
# why are we studying host-pathogen interactions?
# what evidence suggests that modular allelic dependencies might be advantageous in such a host-pathogen system?
# give a one-line description of this type of modularity
# what conditions do we aim to test to show a benefit to modular dependencies/interaction structures?
# what are our null models, i.e. why is (this) result a surprise?
# what impact does this have for the understanding of host-pathogen interactions, and evolvability in general?

=== Proposal Introduction ===

While interactions between species such as hosts and their pathogens (or plants and pollinators, herbivores and plants) have long been implicated as a means of generating patterns of diversification (Ehrlich and Raven 1964; Thompson 1994, 2005), the process by which forces generate robustness and evolvability is not well understood for coevolutionary systems. Previous authors (citation) have suggested that environmental variation leading to temporal changes in fitness can select for modularity in genetic architecture. In the simplest form, Host-pathogen interactions can lead to autocorrelated variation in fitnesses. However, it remains unclear if this type of variation will generate the same kind of selective forces for modularity. These interactions provide an opportunity to study a different form of temporal variation in fitnesses and allow us to test this potentially strong form of selection.

We propose to test whether interactions between coevolving hosts and pathogens provides the conditions necessary for selection for modularity of the pathogen alleles responsible for the interaction with the host. Here we model an abstract interaction between a host and pathogen. In this paper we will compare the selective advantage of pathogens with modularity against pathogens without modularity. The working hypothesis is that antagonistic coevolutionary interactions generate substantial amounts of autocorrelated temporal variation in selection which selects modularity of the pathogen alleles responsible for the interaction with the host.

Model design: We have modeled an antagonistic interaction with two players (host and pathogen). In this system all individuals are haploid. Hosts have only one locus which is the interaction locus with multiple alleles. Pathogens have two loci. Each locus has three alleles. The fitness outcome of an interaction between a host and pathogen is modified by allele combinations at the interaction loci. We have modeled a straightforward case using a inverse matching allele model for the interaction. A match decreases the pathogen’s fitness and increases the host’s fitness. We take an abstract approach and cast this model in terms of replicator dynamics of each player in the interaction.

=== Model Details ===

==== Discrete or continuous? ====
# Pros for discrete: easier to run iterated simulations; possible to run experiments on explicit graph structures
# Pros for continuous: mathematical derivations cleaner

==== Proof of concept ====
Based on an individual based simulation in matlab that I coded up tonight I got a setup that we can work with while we finalize how we want this thing to work.

===== Model Life cycle =====
#'''Infection'''
##Each host is infected with two different pathogens
##This allows limited recombination
#'''Recombination'''
##Given our compatibility matrix of alleles, there is only 2 combinations that will result in more diversity in the host
###X2Y2 and X3Y3 yields all 4 modular genotypes
###X2Y3 and X3Y2 yields all 4 modular genotypes
##None of the other combination result in increased diversity of pathogens within a host
#'''Host-Pathogen fitness interaction'''
##Given our interaction matrix, a match of any host allele will result in detection by the host
###decrease in fitness of the pathogen
###lack of detection results in decrease in fitness of the host
#'''Competition of pathogens'''
##Each of the pathogen genotypes present in the host compete against one another according their fitness after interaction with the host.
###If two pathogens have different fitness, then the one with the greater fitness will dominate that host and exclude the other pathogen.
###If two pathogens have equal fitness, then they will both dominate the host
#'''Replication'''
##Hosts contribute the next generation in proportion to their fitness (it can be decreased by a infection)
##Pathogens contribute to the next generation in proportion to their fitness and the number of other genotypes present in a host.
###If there are two genotypes present in a host, then they each contribute half the amount that a single infection would generate given equal fitness.

===== Diagram of modularity of alleles in Pathogen =====
[[Image:Modv4 compat recb.JPG]]

===== Diagram of interaction between Host and Pathogen =====
[[Image:Modv4 interation.JPG]]

===== Sample dynamics of run =====
Each panel shows a pair of allele frequencies for the match between the host(blue) and pathogen (red). The top two panels show the "non modular" alleles in dashed lines. All six panels show the same set of time in the simulation but the combinations are pulled out separately for clarity. You can see the frequency dependence of the simulation where the pathogen allele will increase in frequency until a host that can detect it become more frequent at which point, that pathogen will decline. Each suscessive wave of increase cycles through the different alleles in both players.

[[Image:Sampledyn.jpg]]

=====Preliminary Results =====
I ran 3 different scenarios with 1000 host individuals in each case. Each run was started with an equal frequency of each host type at a frequency of 1/6. Each run was started with an equal frequency of each pathogen allele (1/3) and the genotype frequencies were 1/3 for x1y1 and 1/6 for the rest. Run were terminated after a single genotype had fixed or 100 generations (very short time, but most fixed quickly). I ran 10,000 replicates and then collected the mean frenquency of each genotype of host and pathogen at the end of the replicate. Plotted are means and <strike>2x st error of the replicates</strike>.

*'''no selection'''
**Case where there was no fitness interactions between the host and pathogen. Drift alone was working here.
*'''random selection'''
**Case where the host frequencies were randomly assigned each generation, but the frequency of the pathogens was dependent on which infections worked in the previous generation.
**This case simulates a kind of randomly variable environment with no autocorrelation.
**There is no cost to modularity in this case. Because the frequencies hosts are being randomly drawn, then over time, each allele should experience the same selective history and so each should have an equal chance of going to fixation.
**Additional, I found that even if I start with extremely skewed allele frequencies (0.1 of X1, .45 X2, .45 X3), I still get the same final distributions of genotypes ((1/3 of P1 and 1/6 of P2-P5) or equal allele frequencies at the end. In some respects it was more telling to start out with unequal frequencies because we see that the random selection provides correction.
*'''selection'''
**Case where alpha/beta were set to 1, so that an infection was lethal to a host and not infecting was lethal to the pathogen.
**Host and Pathogen frequencies were dependent on the selection each imposed on each other (strong frequency dependence)

[[Image:Modv4 resultsb.jpg]]

==== Replicator equations ====
This is just one take at trying to get some handle on the replicator dynamics

[http://www.wsu.edu/~drown/modularity_mathematic_v3.html Replicator Dynamics in Mathematica]

== Glossary ==

=== Evolvability Concepts ===

Some definitions of 'evolvability' drawn from the literature:
#"The capacity of a lineage to evolve has been termed its evolvability, also called evolutionary adaptability. By evolvability, we mean the capacity to generate heritable, selectable phenotypic variation. This capacity may have two components: (i) to reduce the potential lethality of mutations and (ii) to reduce the number of mutations needed to produce phenotypically novel traits" (Kirschner and Gerhart 1998, p. 8420).

=== Modularity Concepts ===

I'm quite sure that there is some overloading here; but these are the types of modularity that have come up in our discussions:
# Modularity for reassortment (Molly)
# Modularity for independence (Molly) (I call this 'functional decomposition' - Rob)
# Repeated modularity: eg where a body segment occurs many times in an organism (Rob)
# Modularity for robustness to antagonistic pleiotrophy (Molly)

Some definitions of 'modularity' drawn from the literature:
#"A module...is a part of an organism that is integrated with respect to a certain kind of process...and relatively autonomous with respect to other parts of the organism" (Wagner et al. 2007, p. 921)
#"All ides of modularity refer to a pattern of connectedness in which elements are grouped into highly connected subsets - that is. modules - which are more loosely connected to other such groups" (Wagner et al. 2007, p. 921)

=== Robustness Concepts ===

Some definitions of 'robustness' drawn from the literature:
#"[R]obustness is the maintenance of specific functionalities of the system against perturbations, and it often requires the system to change its mode of operation in a flexible way. In other words, robustness allows changes in the structure and components of the system owing to perturbations, but specific functions are maintained" (Kitano 2004, p. 827).

=== Pathogen-related terms ===

# '''Epitope ''': the phenotype of a pathogen that interacts with a host
## only need to consider a portion of the host's genome since the pathogen only targets a specialised portion of that genome.

== References ==

Chen Y, Dokholyan N (2006) The coordinated evolution of yeast proteins
is constrained by functional modularity. Trends in Genetics 22:416–419.

D’Auria G, Jim´enez N, Peris-Bondia F, Pelaz C, Latorre A, et al. (2008)
Virulence factor rtx in Legionella pneumophila, evidence suggesting it is a
modular multifunctional protein. BMC Genomics 9:14.[[http://www.pubmedcentral.nih.gov/picrender.fcgi?artid=2257941&blobtype=pdf pdf]]

Early DJ, Deem MW (2004) Evolvability is a selectable trait. Proceedings of the National Academy of Sciences 101:11531-11536 [[http://www.pubmedcentral.nih.gov/picrender.fcgi?artid=511006&blobtype=pdf pdf]]

Hintze A, Adami C (2008) Evolution of complex modular biological networks. PLoS Computational Biology 4:e23.[[http://www.pubmedcentral.nih.gov/picrender.fcgi?artid=2233666&blobtype=pdf pdf]]

Kashtan N, Alon U (2005) Spontaneous evolution of modularity and network
motifs. Proceedings of the National Academy of Sciences 102:13773–
13778.[[http://www.pubmedcentral.nih.gov/picrender.fcgi?artid=1236541&blobtype=pdf pdf]]

Kirschner M, Gerhart J (1998) Evolvability. Proceedings of the National
Academcy of Sciences 95:8420–8427.[[http://www.pubmedcentral.nih.gov/picrender.fcgi?artid=33871&blobtype=pdf pdf]]

Kitano H (2004) Biological robustness. Nature Reviews Genetics 5:826–
837.

Kreimer A, Borenstein E, Gophna U, Ruppin E (2008) The evolution of modularity in bacterial metabolic networks. Proceedings of the National Academy of Sciences 105:6976-6978.

Lynch M (2007) The frailty of adaptive hypotheses for the origins of organismal complexity. Proceedings of the National Academy of Sciences
104:8597–8604.[[http://www.pubmedcentral.nih.gov/picrender.fcgi?artid=1876435&blobtype=pdf pdf]]

Orr, HA (2000) Adaptation and the cost of complexity. Evolution 54:13-20 [[http://www.jstor.org.ezproxy.lib.utexas.edu/stable/pdfplus/2640468.pdf pdf]]

Rives A, Galitski T (2003) Modular organization of cellular networks. Pro-
ceedings of the National Academy of Sciences 100:1128–1133.[[http://www.pubmedcentral.nih.gov/picrender.fcgi?artid=298738&blobtype=pdf pdf]]

Schlosser G, Wagner G (2004) Modularity in Development and Evolution.
Chicago: University of Chicago Press.

Wagner G, Pavlicev M, Cheverud J (2007) The road to modularity. Nature
Reviews Genetics 8:921–931.

Welch JJ, Waxman D (2003) Modularity and the Cost of Complexity. Evolution 57:1723-1734

== Original Discussions ==

#'''Impact of host heterogeneity (= consumer-resource dynamics with identity issues)''': ([[Sarah_Cobey|Sarah]] writes:) Most ecological models of consumer-resource interactions assume that all consumers "view" resources the same way, i.e., each resource has only one possible phenotype. For a host-pathogen system, this means that all hosts agree on which strains are identical and which are different, since all hosts are targeting the same antigenic sites (epitopes) of the pathogen in their immune response. When pathogen strains compete in this environment, a broad range of cool dynamics result ([http://www.scienceonline.org/cgi/content/abstract/280/5365/912 Gupta et al., Science, 1998]), depending on the strength of cross-immunity. There is evidence that hosts do not mount identical immune responses when challenged with the same strain of pathogen. In other words, a pathogen's phenotype is a function of the host. How does heterogeneity in hosts' immune responses--this multiplicity of phenotypes--affect competition among pathogens? These could be important results for the field. I'm thinking of doing some simple nonlinear dynamical analysis that builds on the framework in the Gupta paper. This problem seems broadly extensible to antagonistic interactions more generally, but I can't think of specific biological examples. Anyone interested? (Talk to me or post here!)
##Impact of immune system on host-parasite (/pathogen) interaction
##Seems like you could add some details of host genetics and then make up a matrix that describes the fitness dependences of the pathogens for each host genotype. -Devin
##Interesting paper by [http://www.pnas.org/cgi/content/abstract/104/18/7711 Recker et al (2008)] that could be interesting to discuss on this track as well. -Devin
###Can the Recker article be modified by including extra host compartment to represent different host genotypes?
###I'm not sure we need to add extra compartments, especially if we use a status-based approach with the ODEs. It would be worth talking about this problem in front of a blackboard. How about Thursday evening or Sunday? -[[Sarah_Cobey|Sarah]]
####<strike>Let's discuss 6pm Thursday</strike> completed
##Let's get some pictures of what this would this system would look like. I'll try and add something, but other's should drop in a pdf/powerpoint/artististic rendering
#'''Need homes, or just ideas for later'''
##Effects of pathogen competition on epidemic outbreaks
##Spatial heterogeneity of transmission of parasites-- If we have time, I'd love to put the model we have started to develop on a graph or something...see the effects of spatial heterogeneity and the structure of the population on pathogen population, and maybe see how dynamics differ as one moves from an area of homogenous viral population to a "contact zone" where two strains compete...-[[Molly_Rorick|Molly]]
::*<strike>Infectious diseases: epidemic outbreaks vs. endemic steady states</strike>
::*<strike>Direct vs. vector transmission of parasites/pathogens</strike>
::*<strike>Non-genetic transmission of disease resistance</strike>

#First stab at getting some of our ideas in picture form: [[AII_Modularity]]
#This is very interesting. One could imagine using a (weighted?) network picture to capture the transitions. -- [[Jacob_Foster|Jacob]]
###Right now we have a non-weighted network, but expanding the network to allow variation in edge weight will be a nice extension.--[[Molly_Rorick|Molly]]

I'm not at all a biologist, but perhaps there is some way to quantify modularlity in terms of clusters in these networks? Look at cluster dynamics? Clustering that takes into account link weights (e.g. greater link weight than expected by chance)? Perhaps some of this has been looked at? As in http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1865589 -- [[Laura_Feeney|Laura]]

Epidemiology in general. -[[Ruben_Kubiak|Ruben]]

2008-06-14T13:56:03Z

2008-06-10T01:49:29Z

Drown: AII modularity diagrams

==Antagonistic interspecific interactions==
===Modularity===

Just tossed together some of the ideas we have batting around into some pictures:

[[Image:DMD mod v2 1.JPG]]
[[Image:DMD mod v2 2.JPG]]

CSSS 2008 Santa Fe-Projects & Working Groups

2008-06-10T01:46:55Z

Drown: /* Antagonistic interspecific interactions diagram*/

{{CSSS 2008 Santa Fe}}



== Potential Projects ==

=== Antagonistic interspecific interactions ===
After chatting with several people about host-parasite systems and hearing some of the comments at the icebreaker, I want to see if others are interested in potential projects in this area. As a way of getting some brain storming started, I’ve just typed up some topics (these include ideas I’ve heard from others here at Santa Fe) to see if there is critical mass and an interesting question.

Topics (no particular order)
'''Do we have one or two focal questions?'''
''Is there a desire to combine?''

#'''Impact of host heterogeneity (= consumer-resource dynamics with identity issues)''': ([[Sarah_Cobey|Sarah]] writes:) Most ecological models of consumer-resource interactions assume that all consumers "view" resources the same way, i.e., each resource has only one possible phenotype. For a host-pathogen system, this means that all hosts agree on which strains are identical and which are different, since all hosts are targeting the same antigenic sites (epitopes) of the pathogen in their immune response. When pathogen strains compete in this environment, a broad range of cool dynamics result ([http://www.scienceonline.org/cgi/content/abstract/280/5365/912 Gupta et al., Science, 1998]), depending on the strength of cross-immunity. There is evidence that hosts do not mount identical immune responses when challenged with the same strain of pathogen. In other words, a pathogen's phenotype is a function of the host. How does heterogeneity in hosts' immune responses--this multiplicity of phenotypes--affect competition among pathogens? These could be important results for the field. I'm thinking of doing some simple nonlinear dynamical analysis that builds on the framework in the Gupta paper. This problem seems broadly extensible to antagonistic interactions more generally, but I can't think of specific biological examples. Anyone interested? (Talk to me or post here!)
##Impact of immune system on host-parasite (/pathogen) interaction
##Seems like you could add some details of host genetics and then make up a matrix that describes the fitness dependences of the pathogens for each host genotype. -Devin
##Interesting paper by [http://www.pnas.org/cgi/content/abstract/104/18/7711 Recker et al (2008)] that could be interesting to discuss on this track as well. -Devin
###Can the Recker article be modified by including extra host compartment to represent different host genotypes?
###I'm not sure we need to add extra compartments, especially if we use a status-based approach with the ODEs. It would be worth talking about this problem in front of a blackboard. How about Thursday evening or Sunday? -[[Sarah_Cobey|Sarah]]
####<strike>Let's discuss 6pm Thursday</strike> completed
##Let's get some pictures of what this would this system would look like. I'll try and add something, but other's should drop in a pdf/powerpoint/artististic rendering
#'''Pathogen Modularity''' I would be interested in modeling whether some aspect of pathogen modularity-based evolvability (e.g. "reassortability" or reduced evolutionary constraints between epitopes) significantly affects the evolutionary success of the pathogen. I'd love to incorporate realistic-ish parameters to get a sense for whether this kind of evolvability has a ''significant'' effect on evolutionary success, and if so, whether this significant effect is large enough that we might expect second-order selection for pathogen evolvability. --[[Molly_Rorick|Molly]]
##First stab at getting some of our ideas in picture form: [[AII_Modularity]]
##This is very interesting. One could imagine using a (weighted?) network picture to capture the transitions. -- [[Jacob_Foster|Jacob]]
Right now we have a non-weighted network, but expanding the network to allow variation in edge weight will be a nice extension.--[[Molly_Rorick|Molly]]
#'''Need homes, or just ideas for later'''
##Effects of pathogen competition on epidemic outbreaks
##Spatial heterogeneity of transmission of parasites-- If we have time, I'd love to put the model we have started to develop on a graph or something...see the effects of spatial heterogeneity and the structure of the population on pathogen population, and maybe see how dynamics differ as one moves from an area of homogenous viral population to a "contact zone" where two strains compete...-[[Molly_Rorick|Molly]]
::*<strike>Infectious diseases: epidemic outbreaks vs. endemic steady states</strike>
::*<strike>Direct vs. vector transmission of parasites/pathogens</strike>
::*<strike>Non-genetic transmission of disease resistance</strike>

'''Interested?''' Please add ideas that you find interesting or would like to explore more (or just your name).

-[[Devin_Drown|Devin]]

I'm not at all a biologist, but perhaps there is some way to quantify modularlity in terms of clusters in these networks? Look at cluster dynamics? Clustering that takes into account link weights (e.g. greater link weight than expected by chance)? Perhaps some of this has been looked at? As in http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1865589 -- [[Laura_Feeney|Laura]]

Epidemiology in general. -[[Ruben_Kubiak|Ruben]]

=== Biological Levels / Phenotypes Discussion ===
We have a number of folks here either interested in or studying biology at various levels. I am interested in talking about ways in which it makes sense integrate different levels of biological knowledge into a representation of a system. For example, how might microRNA predictions be combined with gene expression networks (or proteomics or SNPs) to lead to a phenotype.

I am also interested in questions of how phenotypes are defined. Within an organ state (e.g., disease or not) for example, a phenotype might be defined as a gene expression pattern, a growth rate, a panel of microsatellite lengths, or functionally by in vivo or ex vivo capabilities to self-renew, etc. If what we are trying to understand is a larger question of disease or functionality, which phenotypes are interesting and useful (and possible!) to use?

I think these questions can be approached from a variety of ways. Off the top of my head, perhaps multi-scaled modeling or examining the system as a multi-level evolutionary system... I'm sure there are many others.

If you are interested, add your name and we can set up a time / place to talk about these and related questions. Also, please add anything you might want to include in a discussion!!

[[Kathleen_Sprouffske|Kathleen]]

=== Something in Neuroscience ===
I (Nish) would really like to do some more intensive, deep research in Neuroscience (Computational being my perspective). While I am fascinated by neurological and behavioral diseases, I would be open to any kind of neuroscientific problem. Anyone else?

Well, I guess that's my cue! I did my Ph.D. in Neuroscience, and I'd be glad to impart what knowledge I have. What I'd really be interested in is seeing what the interesting problems are which intersect neuroscience and complexity studies. It's surprising, given the obvious complexity of the nervous system, but not many of the articles I read really use this box of tools.

If other people express interest, I could organize a tutorial or small working group where I talk about some of the issues I know about in neuroscience and how they may relate to complexity. (One off the top of my head involves storing and retrieving memories, and is done by [http://www.molbio.princeton.edu/index.php?option=content&task=view&id=335 Carlos Brody] at Princeton; another possibility is applying Network Theory to functional connectivity using some new MRI-based data methods (including [http://en.wikipedia.org/wiki/Diffusion_tensor_imaging Diffusion Tensor Imaging])). But more generally, I think we could expand it to be a "speculative neuroscience" discussion, in which people throw crazy ideas at each other. [[User:Sayres|Sayres]] 18:34, 4 June 2008 (MDT)

- Sounds like fun to me. I think Gerald Edelman and Walter Freeman have done some work in this area, actually, but let's chat (Chris)

- Yeah, I know (some) of Freeman's stuff, but not Edelman's; I just looked him up online. This would be a good opportunity to catch up on some of these ideas. I was introduced to the Freeman ideas earlier, but he hasn't been doing much original research lately, and a lot of the attention is more on his collaborators, like Gyorgy Buszaki (sp?), whose work I would consider more focused on the trees than the forest. :) I myself have studied things at a slightly lower level than Freeman's big-picture ideas, but I think that's what this course is for. I will bring also some work I think is relevant in using forms of network theory to find clustering of objects (as well as in the olfactory system of insects, e.g. [http://laurentlab.caltech.edu/Welcome%20to%20the%20Laurent%20Lab.html Gilles Laurent]), and maybe talk about some newer models of decision making.

I see Nish has a little note below; I'll put some of my responses below there. I'll also go ahead and propose a small tutorial for next week; my plan would be to spend a little time presenting what I know, and encourage people to discuss their own interests. [[User:Sayres|Sayres]] 14:38, 6 June 2008 (MDT)

- yeah, wish I had my books from home here, my memory of Edelman's off the top of my head, but he's real good at synthesizing things (his 2001 book 'a universe of consciousness' is pretty damn good at that, once you get past the popsci intro chapters). Also worth checking out is Peter Gardenfors, and I really like Eric Baum's 'What is Thought?', which though based in computation rather than neurosci, is also great at bringing together so much new research. Terrence Deacon and Merlin Donald's stuff is also excellent, at least on how the evolution of the brain can shed light on these issues. But yeah, let's set up a time to chat on all this.

- This discussion about the storage of short term memory is very interesting. I am interested in finding more realistic models of decision making, e.g. how to model an exploratory process that may eventually lead to a decision? I'm mostly thinking at how to apply these ideas when doing agent based models of social systems. Broad ideas on the architecture of memory in the brain are definitively invaluable! Also, I'm very good at throwing crazy ideas on! Count me in! [[User:Giovanni|Giovanni]]

- Hey Giovanni, sounds good! If you're interested in decision-making, I'd like to direct you to the work of Greg Corrado, a friend and colleague of mine at Stanford. He's done work (with Leo Sugrue and Bill Newsome) on decision-making in tasks where the odds of a choice leading to a reward update dynamically. Here are links to a few of the papers:
* [http://www.jneurosci.org/cgi/content/abstract/27/31/8178 short review article outlining general approaches towards modeling decision-making in neuroscience: a good place to start]
* [http://www.ncbi.nlm.nih.gov/pubmed/15205529?ordinalpos=3&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum Science paper presenting the initial experiments on a simplified foraging task, and trying to understand neural correlates of perceived "value"]
* [http://www.ncbi.nlm.nih.gov/pubmed/16596981?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum theory paper explaining the "LNP" (linear-nonlinear-Poisson) model used to model decision-making processes]

I'll try to talk about this in the tuorial on Wednesday. But in case I don't have time to do it justice (likely), I think their model provides a nice compact description that does a very good job of explaining some complex data. Cheers, [[User:Sayres|Sayres]] 17:35, 9 June 2008 (MDT)

=== Evolving skepticism ===
I'd like to do anything relating to the introduction of misinformation into a system, but one concrete suggestion is looking at how one might evolve a skeptical response to defend against being "defrauded" (this could be in a social science or biological system).

Abby

=== if you can't grow '''Collapse''', you haven't explained it ===
Jared Diamond describes a five point framework for collapse of societies.
These points are:

-resilience of the environment to human caused damage

-climate change

-hostile neighbours

-friendly neighbours

-society's response to its problems

My proposal is to test these points in an agent based setup. we could for example use the parameter sweep etc.

If you are interested, add your name and we can set up a time / place to talk about these and related questions.

[http://www.santafe.edu/events/workshops/index.php/Dirk_van_Apeldoorn Dirk]

I am also very interested in this [http://www.santafe.edu/events/workshops/index.php/Richard_Streeter Richard]

Could we adapt this and include an urban perspective? [http://www.santafe.edu/events/workshops/index.php/Flavia_Feitosa Flávia]

Everybody needs his physicist. :-) - [[Ruben_Kubiak|Ruben]]

I'm interested in this project as well. [http://www.santafe.edu/events/workshops/index.php/Steve_Hall Steve]

I am interested!
[http://www.santafe.edu/events/workshops/index.php/John_Pang John]

Heck yeah! [[Rory_Sayres]] [[User:Sayres|Sayres]] 18:35, 4 June 2008 (MDT)

sounds fun. hope I can be of any help... [http://www.santafe.edu/events/workshops/index.php/Francois_Ascani Francois]

=== Let's make networks secure ===

I'm interested in making 'secure' networks with bound resources (like it is normal in reality). This is a very general questions and has many oppurtunities. For example:

- I have an epidemic and not enough vaccine - who should be vaccinated, who not?

- Terrorist try to smuggle a bomb into the land of Oz. Which flights between which airports should be especially watched to minimize this risk?

- How can we try to secure the internet with special anti-virus hubs? Is it possible to stop the epidemic of computer-viruses by special 'antibody' servers?

This just came to my mind and if anybody has other good ideas or wants to comment this - please feel free.

- [[Ruben_Kubiak|Ruben]]

- How to select nodes in the water system to detect the pollution efficiently?
- How to select individulas in the social network to let advertisement to spread efficiently?
- How to select blog to let people just see a small part of blog and get more information?
Data mining will be useful to analyize huge dataset. [see http://www.cs.cmu.edu/~jure/pubs/detect-kdd07.pdf]
-[[Jiang_Wu|Jiang]]

- Might be interested to see if all these problem can be generalized into a single combinatorial or asymptotic one. What kind of tools would you like to use? (I guess not agents :P) [[User:Giovanni|Giovanni]]

=== Network Security Concepts Inspired by Biological and Social Systems ===
Ruben – Was about to post this when I saw your entry. Sounds like we might have some overlap in our ideas…

One area that I am interested in for a project is applying concepts from biological and social systems to the area of computer network security. This is a broad topic and I am hoping to generate some discussion that might lead to a more well-defined research area.

In the biological area, for example, there have been recent developments in Artificial Immune Systems which borrow techniques from the immune system that enable virus detection and elimination in a self-organized and distributed manner. In particular, Stephanie Forest here at SFI has done work in this area. (see http://www.cs.unm.edu/~forrest/ , http://arxiv.org/ftp/arxiv/papers/0804/0804.1266.pdf) Other interesting research has been done by John Doyle at Caltech in which he compared the “robust yet fragile” organization structures of computer and biological networks (see pages 96-111 http://www.cds.caltech.edu/~doyle/GENSIPS/GENSIPS.pdf , http://www.cds.caltech.edu/~doyle/CmplxNets/)

In the social science area, I have been thinking about trust relationships and how they could apply to computer network security. Trust relationships are well established in computer networks for public key certificates. However, to my knowledge, there is no way to look at the “trust” of pieces of data in a network. Data is often scanned as it enters a network but is not tracked once it is inside to ensure that it behaves properly. This leaves many networks “hard on the outside, but soft and gooey on the inside.” One idea might be to leverage trust/reference concepts in social networks (e.g., eBay, citation networks, Amazon referrals, social websites, etc.) to construct a framework for “trusting” data throughout its lifetime in a network. For example, the more frequently that a piece of data is used effectively by an application might increase its trust. Also see http://www.mindswap.org/papers/Trust.pdf

Please list your name if you have any interest in this topic. Thanks.

Justin Darkoch

I'm happy to help look at this topic, but I suspect that for proper interdisciplinary work you need experts in biology, not computer systems... -- [[Laura_Feeney|Laura]]

=== Incorporating Data into Agent-Based Models ===
The rise of the "omics" fields of biology (e.g., DNA data in genomics, protein data in proteomics, etc) have resulted in a bewildering mass of data. I'm interested in exploring how these data can be incorporated into agent-based modeling strategies. Perhaps the data-mining folks have similar issues?

Perhaps this is a naive question and someone already knows about an instance where this has been successfully accomplished. If so, please forward it along to me!

In any case, I'd like to do anything from just talking about this problem to creating a simple agent-based model that uses publicly-available data. For example, a simple model of bacterial or yeast growth could be coupled with gene expression data from the cell cycle. I'd be very happy to explore any other systems folks are interested in as well.

[[Kathleen_Sprouffske|Kathleen]]

- I understand nothing about biology, but I'm always dealing with empirical data and the challenge of incorporating it to agent-based models. So, maybe we can talk a bit about it. ([http://www.santafe.edu/events/workshops/index.php/Flavia_Feitosa Flavia])

=== A Dance Evolution ===

I'm interested in trying to take Liz Bradly's alphabet dancer (that we saw Monday evening) and seeing if anything interesting/aesthetic could be done in a context where a set of such modeled dancers evolve their choice of movement (and perhaps their location/orientation) based on what their neighbors are doing.

My first thought was to evolve the selection of agent dance movements by analyzing how each selected movement (or perhaps simply their hand positions) temporally/spatially relate to the selected movements of its neighbors.

It might be an interesting context to explore self-organization and the role of conflict and cooperation in producing interesting emergent properties.

I'm thinking the primary work would be done in Netlogo. But I've noticed that Maya can be downloaded for a free 30 day trial period so the result could hopefully be visualized in 3D.

If you're interested leave your name below: [http://www.santafe.edu/events/workshops/index.php/Steve_Hall Steve]

One thing you might want to look at is looking at how dance notation (i.e. formal languages for describing choreograpy) could be used as a basis for "mutation", analogously to mutations on CAGT...
[[Laura_Feeney|Laura]]

=== Some ideas on modeling social media and on multi-agent modeling ===

([[User:Giovanni|Giovanni]]): With the term social media one can indicate the various web 2.0ish communities that are popping out on the internet these days. The following ideas come from watching Wikipedia's users community but I think there are correspondents in the other major social websites, as well on non-internet based communities (e.g. networks of scientific pubblications).
* '''Ownership of encyclopedic articles'''. Wikipedia's policy is that no one can claim ownership on a wiki entry. However, some forms of ownership are sometimes tolerated e.g. when an expert on a certain topic imposes his autority on non-expert editors. While it is generally wise to let the experts user to do this (since you want experts to collaborate to the project), sometimes this can lead to pathological cases in which the "owner" dictatorial methods discourage any other user to do any edit at all. This is a sorta of prisoner's dilemma, since you do not want the expert users to be banished by the community just, but at the same time you want to keep it as open as possible.
* '''Vandalism'''. Given a model in which agents either change the content of a page based on their point of view (these concepts have a precise definition) or revert it to a previous "clean" version, how can a community fight off vandal users? I would like to explore this problem with a "neutral"-like model e.g. in which the social phenomenon of vandalism is just explained in terms of "distance" from a point of view (again, these concepts do need and have a precise definition) and a "culture dependent" model, in which vandals form a population on their own and thus a "vandalic" cultural traits exist and is clearly identifiable by the agents.
* '''Community dynamics in terms of double selective pressure'''. This is a generalization of the previous two. These kind of problems suggest that there is a double selective mechanism by which users are "selected" into the community based on its current status (whatever this thing is), and at the same time the community's status is influenced by the users that live in it. A quick example: a Wikipedia plagued by too many vandals would probably discourage the average user to get in and fight vandalism, which makes life easier for vandals etc.

I would like to explore these problems either with multi-agent simulations or with differential equations. Data are usually not a problem if one wants to study social websites with open API.

On the other side of the MAS-coin, I'm also interested in general methodological problems of Multi-agent systems modeling.
* '''"Evolving" interactions in MAS'''. I talked briefly about that during the brainstorming session of Wednesday. I think some people were interested in that, so better to talk directly.
* '''Causality in MAS simulations and network motifs'''. Here the idea is to look at/develop algorithms to extract network motifs from multi-agent simulations. One has to use a model in which it is already clear what a causal relationship between two events is (I call these also interactions), or at least use the concept of "cause" used in graphical models. Other big question: once one has this kind information, how to use it?

I would be interested in pursuing this. There are some good ins'ights on how this was 'managed' in the development of Linux in Raymond's Cathedral and the Bazaar.
http://www.catb.org/~esr/writings/cathedral-bazaar/cathedral-bazaar/ Talks about that need for the 'inner circle'

Craig

what kind of questions do you want to solve using multi-agent model? Actually, I am really interested in the web2.0 and information diffusion pattern in this kind of web? When is the next meeting? Please add me in this discussion.
Jiangwu.john@gmail.com...[[Jiang_Wu|Jiang]]

=== Financial crisis in Housing Markets ===
After hearing the questions from Dan about market crashes, I got curious about a more recent market crisis, the housing market/home mortgage crunch. Over breakfast a few of us were discussing this and came up with a few questions.-[[Devin_Drown|Devin]]

'''Questions'''
#Is this really a complex system, or just something that is not transparent?
#What really caused our “crisis”?
#What happens if the “Fed” had let Bear Stearns go bankrupt?

'''Comments'''
*The crisis seems to be rooted in a separation between good information at the people who benefit from that information. (Abby)
*Can this be modeled in terms of banks with different risk behaviors/practices? (Devin)
*What about creating a simple ABM model with borrowers and lenders on Netlogo so we can play with heterogenous strategies from the perspective of the firm?(Carlos)
*We can introduce multiple lenders and introduce competition (or collusion?). (John)
*There should be accessible data on this. (John)
*Let's refine the idea. (John) ''see next section''

'''''Back of napkin'' model'''

{|
|-
! Borrow Agents
!
! Lender Agents
!
! Output
|-
|
*Risk profile (credit score)
*Desired loan
*Desired interest rate
| '''<--->'''
* Money
* Information
|
*Risk profile
*Capital constraint
*Interest optimum
*Underwriting rules
|
|
*Distribution of loans
*Default rate (distribution)
*Profits
*Partial equilibrium
*Time Horizon
|}

'''Interested folks'''
*[[Devin_Drown|Devin]]
*Abby
*[[cyepez|Carlos]]
*John Pang
* [[Rory_Sayres | Rory]]

- Hey, just some thoughts on this. Mark Taylor's work on micro/macro finance and crashes in light of complexity economics might be of interest here. He does a great job of explaining the LTCM/Asian tigers crash of 1999. David Harvey's work on the redistribution of crashes via international financial networks as ways of managing accumulation crises also has a lot to offer complexity economics. Eric Beinhocker's work also does a great job of laying out parameters of complexity economics as a whole. My concern about modeling these types of crashes is that modeling a given system can be really decieving, cause really there's an intricate web of complex nets at multiple levels of scale and widely spatially and contextually distributed, all in careful equilibrium, such that minor disturbances in one can trigger a phase change in another, making endogenous analysis problematic. Even the time series analysis done by Mandelbrot and co. in stock markets really does little more than a form of what Liz was doing with expanding 1D time-series of a 3D system, but with a LOT more degrees of freedom at stake. Which isn't to say this sort of modeling doesn't interest me, I just wonder how to do it justice. So, with the Bear Stearns crisis, it seems to me we've got another example of the financial industry coming up with new 'financial products' (in this case, sketchy loans) designed to avoid the fitness conditions provided via market regulation in congress. This leads, as it does everytime the financial sector outwits the regulators (as they do cyclically), to overleveraging of credit, inflation of the market, confidence crisis, government bailout of those who created the bubble, and large scale wealth transfer from low end of the market to the high end. Don't get me wrong, some lose their shirts on the high end, but overall, this sort of 'managed credit crisis' acts as an overall wealth pump from the low end to high end of the market, not due to conscious planning of the crisis on the part of the financiers, but as a macro effect of micro-rules based on outwitting regulators to maximize short range profits. Problem is, though, so many other networks are nested and intertwined here, I mean, how do you take into account shifts in the fitness environment leading to the evolution of new financial technologies, all of which caused the setup for the model in the first place? This problem REALLY interests me, just not sure how to do it in a way that doesn't ignore these complexities. Ideas? [[Christopher Vitale|Chris]]

'''Notes from the margin (6/8/08 - John)'''

We need to keep this fairly simple. We're not trying to model the US economy. Let's stay focused on what questions we're trying to answer.

Two types of agents: borrowers and lenders.

''Borrower''

A borrower agent is described by its credit score. A credit score is an weighted aggregate of the following four attributes of the borrower:

35% — punctuality of payment in the past (only includes payments later than 30 days past due)
30% — the amount of debt, expressed as the ratio of current revolving debt (credit card balances, etc.) to total available revolving credit (credit limits)
15% — length of credit history
10% — types of credit used (installment, revolving, consumer finance)
10% — recent search for credit and/or amount of credit obtained recently

Credit score distribution in the US is:

[[Image: scorerangepercentage.png]]

As a first-order approximation, this can give us the distribution of “risk” profile among borrower agents. Additionally, depending on income (and perhaps credit score itself), value of the property being considered is probably a variable – that is, amount of the loan (certainly, the maximum one can borrow is related to one’s credit score). For the purpose of our model, we should just assume adequate supply of homes fitting the borrower agent’s borrowing capacity. And given the interest rate (and for some people, monthly payment), the borrower agent will either go for the loan or not (and shop around).

We need to also determine an agent’s propensity to borrow – what motivates an agent to decide to purchase a home, and how do we model that?

''Lender''

When a lender agent receives an application for a mortgage, it will process the application according to some pre-specified underwriting rules.

Some good information on underwriting practices can be found at:

[http://en.wikipedia.org/wiki/Mortgage_underwriting_in_the_United_States Underwriting]

Information on subprime lending and subprime crisis can be found at:

[http://en.wikipedia.org/wiki/Subprime_lending Subprime]

We need to come up with a simple algorithm for the lender agent in the model, which will determine if the loan will be made, and if so, return principal amount of the loan and term structure of the loan (fixed or variable interest rate and length of loan – and if the rate is to vary, rules for that). What are the key variables we can tweak to either encourage or discourage non-prime lending?

''And after the loan, so what?''

Certain percent of the loans will default. How do we model this? For the first model, we can assume some percentage of default rate, given the borrower agent’s credit score (hopefully, this data is available). When do they default (first year? Second year?...)? Can we make some simplifying assumptions (e.g., if you don’t default during the first five years, you won’t default, or something like that) for the first model – we can refine the model after we get the first, simple model working.

''Future Refinements we can consider for the model''

Lender agent’s ability to continue lending should be dependent on previous periods default history (some can/should go bankrupt), which should be directly related to its profitability.

Borrower agents will shop around (quality index for lender agent, based on the quality of its portfolio, or perceived "easiness" of getting the loan).

===Dynamics systems applied in networks===
A year or so ago I discovered this researcher[http://www.anarg.jp/~leibnitz/research.php] who uses "Biologically-inspired attractor-selection" methods to route data through a network. It's been a while since I read it, but I believe the idea is to use systems of differential equations to solve networking problems such as finding robust, energy-efficient or shortest paths. I think it would be an interesting project to use both network and differential equations to derive some results, analytical, numerical and simulation. The network need not be a computer network.

Pessimistically, the approach might be just "bullsh*t and hype", but if so, we could analyse and suitably criticise it, and perhaps develop a better approach. Regardless, if anybody is interested, feel free to speak to me (my crap laptop broke recently so I won't be on the net as frequently as usual).

[[Holger Keeler|Paul]]

I think there are a few of us (notably Ruben and myself) that are interested broadly in bio-inspired network stuff (e.g., routing, virus spread, artificial immune systems, etc.) Perhaps we could try to consolidate our interests into a single project. Thoughts? - Justin

Perhaps work by Lidia Yamamoto would be of interest: http://cn.cs.unibas.ch/people/ly/ -- [[Laura_Feeney|Laura]]

I think Kenji Leibnitz' work in bio-routing is conceptually very intersesting, but not entirely convincing from a practical perspective. But I would be happy to meet with people to disucss and look for a project in in this area. [[Laura_Feeney|Laura]]

My computer works again, for the time being. I'm not too focus on biologically-inspired methods necessarily, though they are interesting. I thought this method would be interesting, but now I realise they're stochastic differential equations which don't lend themselves to analysis as easily, I believe. However, it may be possible to ignore the stochastic term. I will sleep on it. Paul

=== Evolving organizational flexibility in dynamic environments ===

Inspired by Josh's model of evolving organizational hierarchy on Thursday, over lunch a few of us discussed how this could be enhanced in several ways. I think that the 'business' in the model can be considered analogous to human societies which have used different organizational structures to cope with differing dynamic environments, and perhaps have corresponding weakness or strengths in said environments. Many geographers/archaeologists consider the level of organizational complexity and inter-linkedness a key part of understanding the resilience and flexibility of a given society.

Some of the ways in which the model may be enhanced are:

# Encode more sophisticated adaptive strategies
# Add a cost of changing institutional structure, perhaps some sort of sunk-cost effect?
# Add more realistic dynamic environments

It is clear from historic human/environment interactions that some societies found it very hard to adapt to changing environmental conditions, and one possible explanation of this is that changing the structure of a society is non-linear process with thresholds, and for vulnerable societies crossing this threshold level was enough to cause collapse.

We could use historic case studies of failure (Norse Greenland, Easter Island) and success (Norse Iceland, many of the other pacific Islands, Japan) and ask, given we know the dynamics of the environment (though palo-environmental reconstruction) if the structure of the society had an impact on the success (or failure, i.e. mal-adaption) of that particular example.

[http://www.santafe.edu/events/workshops/index.php/Richard_Streeter Richard]

I'm interested: [http://www.santafe.edu/events/workshops/index.php/Steve_Hall Steve]

Me too. I'd like to hear about the cases: [http://www.santafe.edu/events/workshops/index.php/Catherine_Spence Cathy]

I can see some parallels between this and the classic tracking problem in control theory. I'd be interested. [[Srideep_Musuvathy|srideep]]

Antony and I have discussed a related problem. There are some recent results in biology relating the fitness cost of developing a sensor system to the entropy of a randomly varying environment. The dynamic environment in Josh's model could be generalized to such an entropy-parameterized environment, and one might expect a transition to the hierarchical structure (which is, more or less, a sensory system) as the entropy varies. [[Jacob_Foster|Jacob]]

===(Bayesian?) learning rates in biological and social systems===
Inspired by David Krakauer's lecture showing that evolution can be seen as a form of Bayesian learning, a question that naturally arises is how to measure learning rates in natural and artificial systems. In economics, [http://en.wikipedia.org/wiki/Experience_curve_effects learning curves and experience curves] are well-documented, typically following a power law shape. Can we quantify '''progress''' in biological, technological, and cultural evolution/development using this framework? Can we use '''efficiency''' as a universal measure? Also: what is the connection with the MEST-compression idea (Matter, Energy, Space, Time) of futurist [http://en.wikipedia.org/wiki/John_Smart_(futurist) John Smart]? (For example, think of future atomic neural nets mentioned by Alfred Hübler as a more compressed form of future intelligence than present state-of-the-art computing machines or brains).
Let me know if you'd like to brainstorm some of these ideas. [[B%C3%A9la_Nagy|Béla]]

=== An agent-based simulation of a pollination network===
Flowers need animals to visit them for reproduction, while these animals visit the flowers for food resources such as nectar. The pattern of interactions between flowers and insects can be thought of as a network of interactions. Different questions emerge in such network:

. What strategies flowers use in order to attract insects? What strategies insects use in order to visit the different flowers?

. What is the explanation for the specialization or the generalization of flowers and insects? why some flowers try to attrack a wide range of pollinators whereas other flowers specialize on a single species?

We would like to make an agent-based simulation based on an evolutionary game theory approach to try to find explanations for such questions and compare it with real data.

[[The pollination network wiki page]]

=== Structure Definitions===

At first sight, it seems obvious what a structure is. However, there are a
lot of different definitions of structure in use - in and between different
communities.

In the first meeting, I (Tanja) informed the others about my motivations for
looking at molecular structures based on RNA features: showing existing
definitions of RNA structure -- for example, minimum free energy, consensus
or abstract shapes, as well as discussing the importance of structure from a
phylogenetic viewpoint.

Moreover, we have had a short discussion about the ''Allegory of the Cave'' by Plato
and started discussing the following papers:

. Structure, Moshe Koppel, 1988

. Form and Content in Thinking Turing Machines, Oswald Wiener, 1988

Both in: The Universal Turing Machine / A Half Century Survey, edited R.
Herken, Springer-Verlag, New York.

We ended up with a lot of questions e.g. about TM, what is a sequence,
minimal descriptions, underlying structures, fundamental
structures, representatives, or the use of definitions in general - e.g
from a historical viewpoint, as well as to categorize them -- e.g. looking
at the purpose.

We already have different viewpoints in our group (e.g. architecture,
information theory, linguistics, logic, philosophy, computer science,
biology). At the last meeting, we decided to start a wiki page to play with
the different definitions between the fields and to prepare our next
meeting.

[[The structure definitions wiki page]]

We have already made an appointment for the second meeting:

9.00 on Wednesday, at Suite 3 (number 39 on the map), upper floor.

Somebody else, e.g from physics?

[[Tanja_Gesell|Tanja]]

I will bring what I can from physics.-- Craig

===Geometry of Fitness Landscapes===
As Dan mentioned today, the geometry of fitness landscapes is relatively unexplored terrain, with most of the underlying trait spaces being either simple (graph) or highly structured (Euclidean) . I've been interested in this topic for a while, so inspired by Dan's comment I thought I'd see if anyone else shared this interest. As a point of departure: there are some interesting articles in the Santa Fe volume on Evolutionary Dynamics, a paper by Stadler, Stadler, Wagner and Fontana (this latter regarding the underlying trait space), and some recent fancy work using computational algebraic geometry (which I don't understand entirely: http://www.biomedcentral.com/1471-2148/7/60/). As a related question, one might imagine exploring the "measurement theory" of fitness landscapes -- how do we reliably reconstruct the landscape geometry from finite measurements?

Anyone interested? (Sorry -- [[Jacob_Foster|Jacob]])

*I can't make out who posted this. I'd be willing to explore this a bit. I have some interested in algebraic topology, computational geometry stuff. However, it is not clear from the paper abstract what kind of 'computational algebraic geometry' they are talking about. [[Srideep_Musuvathy|srideep]]
*I might suggest looking at some of the work by Sergey Gavrilets as a stepping off point for some modern thought from biology on fitness landscapes. Poking around on the web to find a quick summary of some of his thoughts on Holey Adaptive landscapes I found this [http://www.cs.utk.edu/~langston/courses/cs594-fall2003/lecture27.html Lecture] he gave. It's long, but the end slides go into the meat and the begin provides a nice evolution of the ideas. [[Devin_Drown|Devin]]

On a related (but slightly less abstract) note, I am interested in modeling how interacting species co-construct their own and each other's fitness landscapes. I'm imagining an agent based model where each agent has "genes" which specify it's location in a fitness landscape, and also other genes which add some sort of random function to the landscape (as a very crude approximation, one could imagine using a mixture of Gaussians). As the species to evolve, you can watch how they move around in fitness space, and how they deform the landscape. This is an extremely rough idea, but I'd love to sit down and talk with some people about it. Maybe in a related discussion to one posted above.

Any takers? [[David_Foster|David]]
*So in populatoin genetics, I would call this coevolution between two or more players of an interaction (such as host-parasite, or plant and pollinator). Coevolution would occur "where the fitness of both species is affected by the distribution of traits in the other species." [http://dx.doi.org/10.1038/sj.hdy.6800949 (Gomulkiewicz et al 2007)]. I might sugggest looking into some of the coevolution theory literature from such authors as John Thompson, Richard Gomulkiewicz, Scott Nuismer, Sylvain Gandon and Curtis Lively. [[Devin_Drown|Devin]]

Something that came to my mind during the discussion of fitness landscapes was the idea of rate of adaptation to a dynamic fitness landscape. E.g. if the fitness landscape changes (e.g. climate) such that my current local maxima is now becoming a minima, how quickly must I explore the landscape to
esape extinction (dinosaurs seem to have failed this :-) Possibly interesting for both biological (antibiotic resistance, invasive species; climate change) and social systems (evolution of social systems in response to major technological change). Perhaps not enough data to do sensible work.

Any interest? [[Laura_Feeney | Laura]]
* I would say that invasive species provide a rich source of data on this subject as they can end up in an enviroment (and possibly a fitness landscape) that is quite different from their native range. A couple of competing ideas here is that invasives can have rather flat fitness functions with respect to their environment (lots of phenotypic plasticity) or perhaps have enought genetic variation such that an evolved response occurs in the new invaded range. There are of couse invasives that end up modifying the invaded range as well. [[Devin_Drown|Devin]]

== Working Groups ==
=== Summary of Modeling Tools ===
A few of us were talking about how helpful it would be to have a summary of the common and useful modeling tools annotated with their inherent assumptions, best practices, pitfalls, etc. At the moment, we thought we would create a wiki page with this information. Please [[Characterization of Modeling Tools|stop by]] and comment on your favorite tool. In the future, we may bring all interested folks together to discuss and try to come to a consensus.

=== Evolutionary Game Theory ===
A few of us were thinking that there wouldn't be enough time to discuss enough topics in EGT in a [[CSSS_2008_Santa_Fe-Tutorials#A_Crash_Course_to_Classical_and_Evolutionary_Game_Theory|single tutorial]], so I decided to post an offer for a working group that could meet fairly regularly to read and discuss papers from the field, suggest new topics, and possible projects. So far we've thought about looking at evolutionary branching models (in, say, a colony of yeast that produces an enzyme that can be shared by all individuals of the colony) and extending them from one population to two.

Please let me know if you'd be interested in joining. Feel free to add your name and topics you'd like to discuss. 
—-[[User:Jreyes|Josh]]

 Update! This has been scheduled on Friday from 3 - 5, location TBD.

*I'm interested! Actually, I know nothing about the topic, but I think that it could help me in my research. There is an interesting article about segregation and game theory [[Media:Zhang2004.pdf|(Zhang2004)]]. Maybe this could serve as inspiration for a project. (Flavia)
*I'm interested too. [[Kathleen_Sprouffske|Kathleen]]

=== Viral Modelling ===
I (Jeremie) propose to set up a workshop on viral modelling (biomathematics, epidemiology, virus kinetics, evolution, networks...). The idea would be that anyone could prepare a short and general introduction to its research area.
Please let me know if you'd be interested in joining. Feel free to add your name and topics you'd like to discuss.

This sound like fun. All of the above are of interest to me. Alex

I'm interested - Paul

Great idea. I might have some info on computer network virus propagation that I could contribute. - Justin

Ok, I suggest meeting on thursday from 4.30. Let's say we could prepare a 15-20 min tutorial, just to see if we are on the "same page". How does it sound ?

Please put me on any lists for such meetings or tutorials. I am very interested! I have studied quasispecies theory some, but I have no hands-on research experience in any of this. [[Molly_Rorick|Molly]]

=== Social (and other?) Networks ===

There are a number of people who are doing work with or related to social netwworks. Is there interest in a social networks working group? Alternatively, in a more general working group on networks and network based methods (biological, social, etc)?

Show interest and maybe times for a meeting below:

[[User:Laura_Feeney|Laura]] -- I'm free this evening; maybe tomorrow evening before tutorial
[[User:Jeremie Guedj|Jeremie]] -- I'm interested also; free tomorrow evening !

I'd also be interested in this. Tomorrow evening sounds good. [[User: Mark_Rivera | Mark]]

Tentatively scheduled for 7pm -- [[Laura_Feeney|Laura]]

Can we move at 6? I would like to attend Béla's tutorial ... [[User:Giovanni|Giovanni]]

=== Theory Group ===
'''Update (6/08/08):''' Ok, here's the link for [[Theory Group Texts]] page. Post any texts and links you find here so we've got a central clearing house. Some possibilities mentioned were Bruno Latour, Indian philosophy and complexity, etc. Also, '''next meeting''', Tuesday, lunchtime, one of dining hall side tables. So far on agenda - trying to get some of the major terms from the Delanda (strata/network, double articulation, Bwo, agent/operator, intercalary agent, etc.) and discuss further implications of diagram/abstract machine and hierarchy/meshwork distinction.

The general will has spoken and set a rough agenda for our joint exploration of the weird intersections between continental philosophy, critical theory, and complexity. We'll start by reading selections from Manuel De Landa's A Thousand Years of Nonlinear History -- Introduction, Sandstone and Granite, Species and Ecosystems, Arguments and Operators, Conclusions and Speculations. There are several copies floating around (if you have one could you please post here and if you need one do the same). We'll meet Sunday afternoon, to avoid conflict with the hike on Saturday, specific time to be determined.

Update! First meeting 4:20 - 6:00 on Sunday, at the coffee shop/lounge area.

We've discussed several next steps, which I'll post after dinner :)
--[[Jacob_Foster|Hypothetical Hypochondriac]]

- Possible topics we threw around for further discussion - basic working intro to and/or discussion of any of the following thinkers that have been linked to complexity studies - Gilles Deleuze (rhizomatics, diagram/complex assemblages, virtual multiplicities, non-binary theories of language, desiring machines, nomadism vs. state structures, capitalism and desiring-production, major/minor sciences/social groups, networked models of mind, time and duration, intuition as method), Jacques Lacan (matheme-ization of the freudian unconscious, subject/language, master signifiers and social discourse production, ties to topology), Alain Badiou (ethics of the event, ties to cantorian set theory, mathematical ontology), Michel Foucault(decentered subject, disiplinary institutions, biopower, shifting epistemes), C.S. Pierce (process semiotics), Whitehead (process metaphysics), etc. Any ideas/suggestions? (Chris)

Spoken like a true volunteer, Chris! I would very much like an introduction to Deleuze. Peirce and Whitehead would also be fantastic. I would further propose that with many of these thinkers (Deleuze, Lacan, Badiou) we can have some very interesting discussions of the use, misuse, and abuse of technical/mathematical/complexity metaphors outside of the home field (or -- is there even such a thing as abusing a metaphor?) . How can such translation best be achieved? Lacanian mathematics would be an especially interesting angle in my opinion.

Another possibility: Leibniz and the "pre-history" of complexity science! Maybe reading the Monadology, etc.

I believe Tanja will post a link to Krakauer's Metahistory article, to support a broad conversation about History, laws of History, the dangers of such laws, etc.

--[[Jacob_Foster|Hypothetical Hypochondriac]]

Hey All- Ok, found some public domain texts, will keep posting them to my profile page, so far including some Deleuze, Badiou, etc. Chris

Thanks, Chris!
I am looking forward for our discussions about Deleuze and De Landa and
I would very much like an introduction to Lacanian mathematics. Futhermore, I would
also be interested in discussing the Monadology of Leibniz.
As mentioned in the last meeting, it would be nice to take a look at the following paper: The Quest for Patterns in Metahistory, by [http://www.santafe.edu/~krakauer/Site/Reviews_%26_Articles.html. David Krakauer], SFI Bulletin. (2007). In addition, a link to the frescoes in the
[http://www.giottoagliscrovegni.it/eng/home.html Cappella Scrovegni] by Giotto, which I mentioned in the previous meeting.

--[[Tanja_Gesell|Tanja]]

One more link: http://www.netbase.org/delanda/meshwork.htm
MESHWORKS, HIERARCHIES AND INTERFACES

Craig

=== Non-equilibrium thermodynamics and the production of entropy ===
I brought with me the textbook [http://books.google.com/books?id=YRjfuEP_QycC&printsec=frontcover&dq=non-equilibrium+thermodynamics+and+the+production+of+entropy&ei=N19HSP-KCoHIigHFiczqBA&client=firefox-a&sig=sXSiqzPEHeNMOjPuyf986eR6Ljc "Non-equilibrium thermodynamics and the production of entropy" by Kleidon and Lorenz] and I have been trying to understand over the last 6 months what it is all about. The claim is that Nature, whatever in turbulence, life or either markets, tries to maximize the entropy *production*. As Stephen Guerin mentioned earlier this week in one of his lecture, entropy increases but when the system is sufficiently nonlinear, the entropy increases the most rapidly possible. Such overall principle enables to predict the evolution of the system. The book has several chapters showing where his principle could be used: turbulence, mean state of the atmosphere of Earth as well as other planets, the shaping of landscape by water, the coupled evolution of the biosphere and atmosphere, Gaia, economic processes, etc. As long as I do not understand where that principle comes from, I will stay skeptical of those claims. Still, if they are right, this can have important consequences in many fields. Go take a look at the book and if you are interested or if you know something about it, drop me a word. Chuss

[[Francois_Ascani|Francois]]

=== "Speculative" Neuroscience ===
Meet to discuss neuroscience problems and, ideally, cutting edge research. I have Kandel's reference text and Arbib's Handbook with me, and will bring them along for the ride and for background. Would also like to speculate on what's going on in your brain and mind :) Maybe we can meet this weekend sometime, or tonight (5/6) at SFI?

[[Nish_Aravamudan|Nish]]

Hi Nish, I'm interested (see also my notes above). I could meet early this evening, but otherwise I'll be away for the weekend. Please let me know a time for the evening. Otherwise, I'll set up a tutorial (aiming for a Wednesday AM time next week -- that work for you?) and see if there's interest among other folks. Cheers, [[User:Sayres|Sayres]] 14:41, 6 June 2008 (MDT)

I'd be interested in throwing my thoughts around. I am not sure if you are going to discuss ideas at a neuronal modeling and analysis level or the behaviour and organization of a network of neurons. [[Srideep_Musuvathy|srideep]]

I already went through most of the Kandell textbook during a reading group last year and I would like to discuss more some new stuff like mirror neurons which in that textbook were not present, as well the biochemical aspects of the brain, which we ashamelessly skipped since most of the people in the group were AI folks! [[User:Giovanni|Giovanni]]

Count me in! [[Christopher Vitale|Chris]]

== BrainStorming Projects ==

=== Peter ===

Emergence of language in an agent-based model
*I am still interested(Petr).

=== Giovanni ===

"Evolving" interactions in M.A.S. (See above my project ideas) [[User:Giovanni|Giovanni]]

=== Riley ===

Prediction in cultural markets

=== Abby ===

Misinformation

=== Antony ===

Time-horizon of political institutions for managing global environmental goods

=== Mark ===

Social network data/evolution of networks

=== Skyler ===

Networks plus application of biological methods

=== Qiqi ===

Public goods gam, group cooperation, social network

...> group behaviour of CSSS 2008 
gathering data from all of us, including game theory and perhaps agent based modeling 

=== Tanja ===

Structure definitions

=== Jon ===

- Epidemic models of depression/anxiety
- Inference of stochastic models

=== Rio ===

Social-ecological system -> Resilience institutions

=== Flávia ===

Emergence of segregation from a game theory perspective.

=== Francois ===

1) I have a time series of Chlorophyll a taken over 20 years. A Nature paper has claimed that a chaotic model reproduce the observed time series. Simple question: is there any evidence that the observed time series itself be chaotic? That would be a simple application of the Nonlinear Time Series Analysis introduced by Liz. May just be a nice exercise to do, not necessarily a final project. let me know if interesting in helping me.

2) Lattice-Botlzmann models are quite like the Agent-Based models but they seem better adapted to reproduce fluids in motion: the code is short and I have a couple of them that I got from open sources. I never used them but if anybody is interested to play with it, let me know. we could use the sand table that Redfish has and maybe reproduce some cool stuff such as the flooding of a valley, the breaking of a dam, or something like that!

3) what about the climate? nobody interested? this is one of the most *complex* system. we could try our hands on simple conceptual model of the climate?

[[Francois_Ascani|Francois]]

Hi, Francois. I'd be interested in helping with (1). Would love to speculate about (3), though I don't have much background. -[[Sarah_Cobey|Sarah]]

(1) Sounds interesting - The unAustralian Paul

I've had some experience in dealing with problems similar to (1). (3) is an interesting problem - we could play around with the lorenz equation or look at temperature data. I might be interested in in exploring the question as to whether 'global warming' can be reduced or if we were to try and reduce it, can we be certain that we do not over react! This is an interesting problem and I would like to get my feet wet in this sea of ideas. [[Srideep_Musuvathy|srideep]]

File:DMD mod v2 2.JPG

2008-06-10T01:43:17Z

Drown:

File:DMD mod v2 1.JPG

2008-06-10T01:42:12Z

Drown:

CSSS 2008 Santa Fe-Projects & Working Groups

2008-06-10T01:29:10Z

Drown: /* Geometry of Fitness Landscapes */

{{CSSS 2008 Santa Fe}}



== Potential Projects ==

=== Antagonistic interspecific interactions ===
After chatting with several people about host-parasite systems and hearing some of the comments at the icebreaker, I want to see if others are interested in potential projects in this area. As a way of getting some brain storming started, I’ve just typed up some topics (these include ideas I’ve heard from others here at Santa Fe) to see if there is critical mass and an interesting question.

Topics (no particular order)
'''Do we have one or two focal questions?'''
''Is there a desire to combine?''

#'''Impact of host heterogeneity (= consumer-resource dynamics with identity issues)''': ([[Sarah_Cobey|Sarah]] writes:) Most ecological models of consumer-resource interactions assume that all consumers "view" resources the same way, i.e., each resource has only one possible phenotype. For a host-pathogen system, this means that all hosts agree on which strains are identical and which are different, since all hosts are targeting the same antigenic sites (epitopes) of the pathogen in their immune response. When pathogen strains compete in this environment, a broad range of cool dynamics result ([http://www.scienceonline.org/cgi/content/abstract/280/5365/912 Gupta et al., Science, 1998]), depending on the strength of cross-immunity. There is evidence that hosts do not mount identical immune responses when challenged with the same strain of pathogen. In other words, a pathogen's phenotype is a function of the host. How does heterogeneity in hosts' immune responses--this multiplicity of phenotypes--affect competition among pathogens? These could be important results for the field. I'm thinking of doing some simple nonlinear dynamical analysis that builds on the framework in the Gupta paper. This problem seems broadly extensible to antagonistic interactions more generally, but I can't think of specific biological examples. Anyone interested? (Talk to me or post here!)
##Impact of immune system on host-parasite (/pathogen) interaction
##Seems like you could add some details of host genetics and then make up a matrix that describes the fitness dependences of the pathogens for each host genotype. -Devin
##Interesting paper by [http://www.pnas.org/cgi/content/abstract/104/18/7711 Recker et al (2008)] that could be interesting to discuss on this track as well. -Devin
###Can the Recker article be modified by including extra host compartment to represent different host genotypes?
###I'm not sure we need to add extra compartments, especially if we use a status-based approach with the ODEs. It would be worth talking about this problem in front of a blackboard. How about Thursday evening or Sunday? -[[Sarah_Cobey|Sarah]]
####<strike>Let's discuss 6pm Thursday</strike> completed
##Let's get some pictures of what this would this system would look like. I'll try and add something, but other's should drop in a pdf/powerpoint/artististic rendering
#'''Pathogen Modularity''' I would be interested in modeling whether some aspect of pathogen modularity-based evolvability (e.g. "reassortability" or reduced evolutionary constraints between epitopes) significantly affects the evolutionary success of the pathogen. I'd love to incorporate realistic-ish parameters to get a sense for whether this kind of evolvability has a ''significant'' effect on evolutionary success, and if so, whether this significant effect is large enough that we might expect second-order selection for pathogen evolvability. --[[Molly_Rorick|Molly]]
##Let's get some pictures of what this would this system would look like.
##This is very interesting. One could imagine using a (weighted?) network picture to capture the transitions. -- [[Jacob_Foster|Jacob]]
Right now we have a non-weighted network, but expanding the network to allow variation in edge weight will be a nice extension.--[[Molly_Rorick|Molly]]
#'''Need homes, or just ideas for later'''
##Effects of pathogen competition on epidemic outbreaks
##Spatial heterogeneity of transmission of parasites-- If we have time, I'd love to put the model we have started to develop on a graph or something...see the effects of spatial heterogeneity and the structure of the population on pathogen population, and maybe see how dynamics differ as one moves from an area of homogenous viral population to a "contact zone" where two strains compete...-[[Molly_Rorick|Molly]]
::*<strike>Infectious diseases: epidemic outbreaks vs. endemic steady states</strike>
::*<strike>Direct vs. vector transmission of parasites/pathogens</strike>
::*<strike>Non-genetic transmission of disease resistance</strike>

'''Interested?''' Please add ideas that you find interesting or would like to explore more (or just your name).

-[[Devin_Drown|Devin]]

I'm not at all a biologist, but perhaps there is some way to quantify modularlity in terms of clusters in these networks? Look at cluster dynamics? Clustering that takes into account link weights (e.g. greater link weight than expected by chance)? Perhaps some of this has been looked at? As in http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1865589 -- [[Laura_Feeney|Laura]]

Epidemiology in general. -[[Ruben_Kubiak|Ruben]]

=== Biological Levels / Phenotypes Discussion ===
We have a number of folks here either interested in or studying biology at various levels. I am interested in talking about ways in which it makes sense integrate different levels of biological knowledge into a representation of a system. For example, how might microRNA predictions be combined with gene expression networks (or proteomics or SNPs) to lead to a phenotype.

I am also interested in questions of how phenotypes are defined. Within an organ state (e.g., disease or not) for example, a phenotype might be defined as a gene expression pattern, a growth rate, a panel of microsatellite lengths, or functionally by in vivo or ex vivo capabilities to self-renew, etc. If what we are trying to understand is a larger question of disease or functionality, which phenotypes are interesting and useful (and possible!) to use?

I think these questions can be approached from a variety of ways. Off the top of my head, perhaps multi-scaled modeling or examining the system as a multi-level evolutionary system... I'm sure there are many others.

If you are interested, add your name and we can set up a time / place to talk about these and related questions. Also, please add anything you might want to include in a discussion!!

[[Kathleen_Sprouffske|Kathleen]]

=== Something in Neuroscience ===
I (Nish) would really like to do some more intensive, deep research in Neuroscience (Computational being my perspective). While I am fascinated by neurological and behavioral diseases, I would be open to any kind of neuroscientific problem. Anyone else?

Well, I guess that's my cue! I did my Ph.D. in Neuroscience, and I'd be glad to impart what knowledge I have. What I'd really be interested in is seeing what the interesting problems are which intersect neuroscience and complexity studies. It's surprising, given the obvious complexity of the nervous system, but not many of the articles I read really use this box of tools.

If other people express interest, I could organize a tutorial or small working group where I talk about some of the issues I know about in neuroscience and how they may relate to complexity. (One off the top of my head involves storing and retrieving memories, and is done by [http://www.molbio.princeton.edu/index.php?option=content&task=view&id=335 Carlos Brody] at Princeton; another possibility is applying Network Theory to functional connectivity using some new MRI-based data methods (including [http://en.wikipedia.org/wiki/Diffusion_tensor_imaging Diffusion Tensor Imaging])). But more generally, I think we could expand it to be a "speculative neuroscience" discussion, in which people throw crazy ideas at each other. [[User:Sayres|Sayres]] 18:34, 4 June 2008 (MDT)

- Sounds like fun to me. I think Gerald Edelman and Walter Freeman have done some work in this area, actually, but let's chat (Chris)

- Yeah, I know (some) of Freeman's stuff, but not Edelman's; I just looked him up online. This would be a good opportunity to catch up on some of these ideas. I was introduced to the Freeman ideas earlier, but he hasn't been doing much original research lately, and a lot of the attention is more on his collaborators, like Gyorgy Buszaki (sp?), whose work I would consider more focused on the trees than the forest. :) I myself have studied things at a slightly lower level than Freeman's big-picture ideas, but I think that's what this course is for. I will bring also some work I think is relevant in using forms of network theory to find clustering of objects (as well as in the olfactory system of insects, e.g. [http://laurentlab.caltech.edu/Welcome%20to%20the%20Laurent%20Lab.html Gilles Laurent]), and maybe talk about some newer models of decision making.

I see Nish has a little note below; I'll put some of my responses below there. I'll also go ahead and propose a small tutorial for next week; my plan would be to spend a little time presenting what I know, and encourage people to discuss their own interests. [[User:Sayres|Sayres]] 14:38, 6 June 2008 (MDT)

- yeah, wish I had my books from home here, my memory of Edelman's off the top of my head, but he's real good at synthesizing things (his 2001 book 'a universe of consciousness' is pretty damn good at that, once you get past the popsci intro chapters). Also worth checking out is Peter Gardenfors, and I really like Eric Baum's 'What is Thought?', which though based in computation rather than neurosci, is also great at bringing together so much new research. Terrence Deacon and Merlin Donald's stuff is also excellent, at least on how the evolution of the brain can shed light on these issues. But yeah, let's set up a time to chat on all this.

- This discussion about the storage of short term memory is very interesting. I am interested in finding more realistic models of decision making, e.g. how to model an exploratory process that may eventually lead to a decision? I'm mostly thinking at how to apply these ideas when doing agent based models of social systems. Broad ideas on the architecture of memory in the brain are definitively invaluable! Also, I'm very good at throwing crazy ideas on! Count me in! [[User:Giovanni|Giovanni]]

- Hey Giovanni, sounds good! If you're interested in decision-making, I'd like to direct you to the work of Greg Corrado, a friend and colleague of mine at Stanford. He's done work (with Leo Sugrue and Bill Newsome) on decision-making in tasks where the odds of a choice leading to a reward update dynamically. Here are links to a few of the papers:
* [http://www.jneurosci.org/cgi/content/abstract/27/31/8178 short review article outlining general approaches towards modeling decision-making in neuroscience: a good place to start]
* [http://www.ncbi.nlm.nih.gov/pubmed/15205529?ordinalpos=3&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum Science paper presenting the initial experiments on a simplified foraging task, and trying to understand neural correlates of perceived "value"]
* [http://www.ncbi.nlm.nih.gov/pubmed/16596981?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum theory paper explaining the "LNP" (linear-nonlinear-Poisson) model used to model decision-making processes]

I'll try to talk about this in the tuorial on Wednesday. But in case I don't have time to do it justice (likely), I think their model provides a nice compact description that does a very good job of explaining some complex data. Cheers, [[User:Sayres|Sayres]] 17:35, 9 June 2008 (MDT)

=== Evolving skepticism ===
I'd like to do anything relating to the introduction of misinformation into a system, but one concrete suggestion is looking at how one might evolve a skeptical response to defend against being "defrauded" (this could be in a social science or biological system).

Abby

=== if you can't grow '''Collapse''', you haven't explained it ===
Jared Diamond describes a five point framework for collapse of societies.
These points are:

-resilience of the environment to human caused damage

-climate change

-hostile neighbours

-friendly neighbours

-society's response to its problems

My proposal is to test these points in an agent based setup. we could for example use the parameter sweep etc.

If you are interested, add your name and we can set up a time / place to talk about these and related questions.

[http://www.santafe.edu/events/workshops/index.php/Dirk_van_Apeldoorn Dirk]

I am also very interested in this [http://www.santafe.edu/events/workshops/index.php/Richard_Streeter Richard]

Could we adapt this and include an urban perspective? [http://www.santafe.edu/events/workshops/index.php/Flavia_Feitosa Flávia]

Everybody needs his physicist. :-) - [[Ruben_Kubiak|Ruben]]

I'm interested in this project as well. [http://www.santafe.edu/events/workshops/index.php/Steve_Hall Steve]

I am interested!
[http://www.santafe.edu/events/workshops/index.php/John_Pang John]

Heck yeah! [[Rory_Sayres]] [[User:Sayres|Sayres]] 18:35, 4 June 2008 (MDT)

sounds fun. hope I can be of any help... [http://www.santafe.edu/events/workshops/index.php/Francois_Ascani Francois]

=== Let's make networks secure ===

I'm interested in making 'secure' networks with bound resources (like it is normal in reality). This is a very general questions and has many oppurtunities. For example:

- I have an epidemic and not enough vaccine - who should be vaccinated, who not?

- Terrorist try to smuggle a bomb into the land of Oz. Which flights between which airports should be especially watched to minimize this risk?

- How can we try to secure the internet with special anti-virus hubs? Is it possible to stop the epidemic of computer-viruses by special 'antibody' servers?

This just came to my mind and if anybody has other good ideas or wants to comment this - please feel free.

- [[Ruben_Kubiak|Ruben]]

- How to select nodes in the water system to detect the pollution efficiently?
- How to select individulas in the social network to let advertisement to spread efficiently?
- How to select blog to let people just see a small part of blog and get more information?
Data mining will be useful to analyize huge dataset. [see http://www.cs.cmu.edu/~jure/pubs/detect-kdd07.pdf]
-[[Jiang_Wu|Jiang]]

- Might be interested to see if all these problem can be generalized into a single combinatorial or asymptotic one. What kind of tools would you like to use? (I guess not agents :P) [[User:Giovanni|Giovanni]]

=== Network Security Concepts Inspired by Biological and Social Systems ===
Ruben – Was about to post this when I saw your entry. Sounds like we might have some overlap in our ideas…

One area that I am interested in for a project is applying concepts from biological and social systems to the area of computer network security. This is a broad topic and I am hoping to generate some discussion that might lead to a more well-defined research area.

In the biological area, for example, there have been recent developments in Artificial Immune Systems which borrow techniques from the immune system that enable virus detection and elimination in a self-organized and distributed manner. In particular, Stephanie Forest here at SFI has done work in this area. (see http://www.cs.unm.edu/~forrest/ , http://arxiv.org/ftp/arxiv/papers/0804/0804.1266.pdf) Other interesting research has been done by John Doyle at Caltech in which he compared the “robust yet fragile” organization structures of computer and biological networks (see pages 96-111 http://www.cds.caltech.edu/~doyle/GENSIPS/GENSIPS.pdf , http://www.cds.caltech.edu/~doyle/CmplxNets/)

In the social science area, I have been thinking about trust relationships and how they could apply to computer network security. Trust relationships are well established in computer networks for public key certificates. However, to my knowledge, there is no way to look at the “trust” of pieces of data in a network. Data is often scanned as it enters a network but is not tracked once it is inside to ensure that it behaves properly. This leaves many networks “hard on the outside, but soft and gooey on the inside.” One idea might be to leverage trust/reference concepts in social networks (e.g., eBay, citation networks, Amazon referrals, social websites, etc.) to construct a framework for “trusting” data throughout its lifetime in a network. For example, the more frequently that a piece of data is used effectively by an application might increase its trust. Also see http://www.mindswap.org/papers/Trust.pdf

Please list your name if you have any interest in this topic. Thanks.

Justin Darkoch

I'm happy to help look at this topic, but I suspect that for proper interdisciplinary work you need experts in biology, not computer systems... -- [[Laura_Feeney|Laura]]

=== Incorporating Data into Agent-Based Models ===
The rise of the "omics" fields of biology (e.g., DNA data in genomics, protein data in proteomics, etc) have resulted in a bewildering mass of data. I'm interested in exploring how these data can be incorporated into agent-based modeling strategies. Perhaps the data-mining folks have similar issues?

Perhaps this is a naive question and someone already knows about an instance where this has been successfully accomplished. If so, please forward it along to me!

In any case, I'd like to do anything from just talking about this problem to creating a simple agent-based model that uses publicly-available data. For example, a simple model of bacterial or yeast growth could be coupled with gene expression data from the cell cycle. I'd be very happy to explore any other systems folks are interested in as well.

[[Kathleen_Sprouffske|Kathleen]]

- I understand nothing about biology, but I'm always dealing with empirical data and the challenge of incorporating it to agent-based models. So, maybe we can talk a bit about it. ([http://www.santafe.edu/events/workshops/index.php/Flavia_Feitosa Flavia])

=== A Dance Evolution ===

I'm interested in trying to take Liz Bradly's alphabet dancer (that we saw Monday evening) and seeing if anything interesting/aesthetic could be done in a context where a set of such modeled dancers evolve their choice of movement (and perhaps their location/orientation) based on what their neighbors are doing.

My first thought was to evolve the selection of agent dance movements by analyzing how each selected movement (or perhaps simply their hand positions) temporally/spatially relate to the selected movements of its neighbors.

It might be an interesting context to explore self-organization and the role of conflict and cooperation in producing interesting emergent properties.

I'm thinking the primary work would be done in Netlogo. But I've noticed that Maya can be downloaded for a free 30 day trial period so the result could hopefully be visualized in 3D.

If you're interested leave your name below: [http://www.santafe.edu/events/workshops/index.php/Steve_Hall Steve]

One thing you might want to look at is looking at how dance notation (i.e. formal languages for describing choreograpy) could be used as a basis for "mutation", analogously to mutations on CAGT...
[[Laura_Feeney|Laura]]

=== Some ideas on modeling social media and on multi-agent modeling ===

([[User:Giovanni|Giovanni]]): With the term social media one can indicate the various web 2.0ish communities that are popping out on the internet these days. The following ideas come from watching Wikipedia's users community but I think there are correspondents in the other major social websites, as well on non-internet based communities (e.g. networks of scientific pubblications).
* '''Ownership of encyclopedic articles'''. Wikipedia's policy is that no one can claim ownership on a wiki entry. However, some forms of ownership are sometimes tolerated e.g. when an expert on a certain topic imposes his autority on non-expert editors. While it is generally wise to let the experts user to do this (since you want experts to collaborate to the project), sometimes this can lead to pathological cases in which the "owner" dictatorial methods discourage any other user to do any edit at all. This is a sorta of prisoner's dilemma, since you do not want the expert users to be banished by the community just, but at the same time you want to keep it as open as possible.
* '''Vandalism'''. Given a model in which agents either change the content of a page based on their point of view (these concepts have a precise definition) or revert it to a previous "clean" version, how can a community fight off vandal users? I would like to explore this problem with a "neutral"-like model e.g. in which the social phenomenon of vandalism is just explained in terms of "distance" from a point of view (again, these concepts do need and have a precise definition) and a "culture dependent" model, in which vandals form a population on their own and thus a "vandalic" cultural traits exist and is clearly identifiable by the agents.
* '''Community dynamics in terms of double selective pressure'''. This is a generalization of the previous two. These kind of problems suggest that there is a double selective mechanism by which users are "selected" into the community based on its current status (whatever this thing is), and at the same time the community's status is influenced by the users that live in it. A quick example: a Wikipedia plagued by too many vandals would probably discourage the average user to get in and fight vandalism, which makes life easier for vandals etc.

I would like to explore these problems either with multi-agent simulations or with differential equations. Data are usually not a problem if one wants to study social websites with open API.

On the other side of the MAS-coin, I'm also interested in general methodological problems of Multi-agent systems modeling.
* '''"Evolving" interactions in MAS'''. I talked briefly about that during the brainstorming session of Wednesday. I think some people were interested in that, so better to talk directly.
* '''Causality in MAS simulations and network motifs'''. Here the idea is to look at/develop algorithms to extract network motifs from multi-agent simulations. One has to use a model in which it is already clear what a causal relationship between two events is (I call these also interactions), or at least use the concept of "cause" used in graphical models. Other big question: once one has this kind information, how to use it?

I would be interested in pursuing this. There are some good ins'ights on how this was 'managed' in the development of Linux in Raymond's Cathedral and the Bazaar.
http://www.catb.org/~esr/writings/cathedral-bazaar/cathedral-bazaar/ Talks about that need for the 'inner circle'

Craig

what kind of questions do you want to solve using multi-agent model? Actually, I am really interested in the web2.0 and information diffusion pattern in this kind of web? When is the next meeting? Please add me in this discussion.
Jiangwu.john@gmail.com...[[Jiang_Wu|Jiang]]

=== Financial crisis in Housing Markets ===
After hearing the questions from Dan about market crashes, I got curious about a more recent market crisis, the housing market/home mortgage crunch. Over breakfast a few of us were discussing this and came up with a few questions.-[[Devin_Drown|Devin]]

'''Questions'''
#Is this really a complex system, or just something that is not transparent?
#What really caused our “crisis”?
#What happens if the “Fed” had let Bear Stearns go bankrupt?

'''Comments'''
*The crisis seems to be rooted in a separation between good information at the people who benefit from that information. (Abby)
*Can this be modeled in terms of banks with different risk behaviors/practices? (Devin)
*What about creating a simple ABM model with borrowers and lenders on Netlogo so we can play with heterogenous strategies from the perspective of the firm?(Carlos)
*We can introduce multiple lenders and introduce competition (or collusion?). (John)
*There should be accessible data on this. (John)
*Let's refine the idea. (John) ''see next section''

'''''Back of napkin'' model'''

{|
|-
! Borrow Agents
!
! Lender Agents
!
! Output
|-
|
*Risk profile (credit score)
*Desired loan
*Desired interest rate
| '''<--->'''
* Money
* Information
|
*Risk profile
*Capital constraint
*Interest optimum
*Underwriting rules
|
|
*Distribution of loans
*Default rate (distribution)
*Profits
*Partial equilibrium
*Time Horizon
|}

'''Interested folks'''
*[[Devin_Drown|Devin]]
*Abby
*[[cyepez|Carlos]]
*John Pang
* [[Rory_Sayres | Rory]]

- Hey, just some thoughts on this. Mark Taylor's work on micro/macro finance and crashes in light of complexity economics might be of interest here. He does a great job of explaining the LTCM/Asian tigers crash of 1999. David Harvey's work on the redistribution of crashes via international financial networks as ways of managing accumulation crises also has a lot to offer complexity economics. Eric Beinhocker's work also does a great job of laying out parameters of complexity economics as a whole. My concern about modeling these types of crashes is that modeling a given system can be really decieving, cause really there's an intricate web of complex nets at multiple levels of scale and widely spatially and contextually distributed, all in careful equilibrium, such that minor disturbances in one can trigger a phase change in another, making endogenous analysis problematic. Even the time series analysis done by Mandelbrot and co. in stock markets really does little more than a form of what Liz was doing with expanding 1D time-series of a 3D system, but with a LOT more degrees of freedom at stake. Which isn't to say this sort of modeling doesn't interest me, I just wonder how to do it justice. So, with the Bear Stearns crisis, it seems to me we've got another example of the financial industry coming up with new 'financial products' (in this case, sketchy loans) designed to avoid the fitness conditions provided via market regulation in congress. This leads, as it does everytime the financial sector outwits the regulators (as they do cyclically), to overleveraging of credit, inflation of the market, confidence crisis, government bailout of those who created the bubble, and large scale wealth transfer from low end of the market to the high end. Don't get me wrong, some lose their shirts on the high end, but overall, this sort of 'managed credit crisis' acts as an overall wealth pump from the low end to high end of the market, not due to conscious planning of the crisis on the part of the financiers, but as a macro effect of micro-rules based on outwitting regulators to maximize short range profits. Problem is, though, so many other networks are nested and intertwined here, I mean, how do you take into account shifts in the fitness environment leading to the evolution of new financial technologies, all of which caused the setup for the model in the first place? This problem REALLY interests me, just not sure how to do it in a way that doesn't ignore these complexities. Ideas? [[Christopher Vitale|Chris]]

'''Notes from the margin (6/8/08 - John)'''

We need to keep this fairly simple. We're not trying to model the US economy. Let's stay focused on what questions we're trying to answer.

Two types of agents: borrowers and lenders.

''Borrower''

A borrower agent is described by its credit score. A credit score is an weighted aggregate of the following four attributes of the borrower:

35% — punctuality of payment in the past (only includes payments later than 30 days past due)
30% — the amount of debt, expressed as the ratio of current revolving debt (credit card balances, etc.) to total available revolving credit (credit limits)
15% — length of credit history
10% — types of credit used (installment, revolving, consumer finance)
10% — recent search for credit and/or amount of credit obtained recently

Credit score distribution in the US is:

[[Image: scorerangepercentage.png]]

As a first-order approximation, this can give us the distribution of “risk” profile among borrower agents. Additionally, depending on income (and perhaps credit score itself), value of the property being considered is probably a variable – that is, amount of the loan (certainly, the maximum one can borrow is related to one’s credit score). For the purpose of our model, we should just assume adequate supply of homes fitting the borrower agent’s borrowing capacity. And given the interest rate (and for some people, monthly payment), the borrower agent will either go for the loan or not (and shop around).

We need to also determine an agent’s propensity to borrow – what motivates an agent to decide to purchase a home, and how do we model that?

''Lender''

When a lender agent receives an application for a mortgage, it will process the application according to some pre-specified underwriting rules.

Some good information on underwriting practices can be found at:

[http://en.wikipedia.org/wiki/Mortgage_underwriting_in_the_United_States Underwriting]

Information on subprime lending and subprime crisis can be found at:

[http://en.wikipedia.org/wiki/Subprime_lending Subprime]

We need to come up with a simple algorithm for the lender agent in the model, which will determine if the loan will be made, and if so, return principal amount of the loan and term structure of the loan (fixed or variable interest rate and length of loan – and if the rate is to vary, rules for that). What are the key variables we can tweak to either encourage or discourage non-prime lending?

''And after the loan, so what?''

Certain percent of the loans will default. How do we model this? For the first model, we can assume some percentage of default rate, given the borrower agent’s credit score (hopefully, this data is available). When do they default (first year? Second year?...)? Can we make some simplifying assumptions (e.g., if you don’t default during the first five years, you won’t default, or something like that) for the first model – we can refine the model after we get the first, simple model working.

''Future Refinements we can consider for the model''

Lender agent’s ability to continue lending should be dependent on previous periods default history (some can/should go bankrupt), which should be directly related to its profitability.

Borrower agents will shop around (quality index for lender agent, based on the quality of its portfolio, or perceived "easiness" of getting the loan).

===Dynamics systems applied in networks===
A year or so ago I discovered this researcher[http://www.anarg.jp/~leibnitz/research.php] who uses "Biologically-inspired attractor-selection" methods to route data through a network. It's been a while since I read it, but I believe the idea is to use systems of differential equations to solve networking problems such as finding robust, energy-efficient or shortest paths. I think it would be an interesting project to use both network and differential equations to derive some results, analytical, numerical and simulation. The network need not be a computer network.

Pessimistically, the approach might be just "bullsh*t and hype", but if so, we could analyse and suitably criticise it, and perhaps develop a better approach. Regardless, if anybody is interested, feel free to speak to me (my crap laptop broke recently so I won't be on the net as frequently as usual).

[[Holger Keeler|Paul]]

I think there are a few of us (notably Ruben and myself) that are interested broadly in bio-inspired network stuff (e.g., routing, virus spread, artificial immune systems, etc.) Perhaps we could try to consolidate our interests into a single project. Thoughts? - Justin

Perhaps work by Lidia Yamamoto would be of interest: http://cn.cs.unibas.ch/people/ly/ -- [[Laura_Feeney|Laura]]

I think Kenji Leibnitz' work in bio-routing is conceptually very intersesting, but not entirely convincing from a practical perspective. But I would be happy to meet with people to disucss and look for a project in in this area. [[Laura_Feeney|Laura]]

My computer works again, for the time being. I'm not too focus on biologically-inspired methods necessarily, though they are interesting. I thought this method would be interesting, but now I realise they're stochastic differential equations which don't lend themselves to analysis as easily, I believe. However, it may be possible to ignore the stochastic term. I will sleep on it. Paul

=== Evolving organizational flexibility in dynamic environments ===

Inspired by Josh's model of evolving organizational hierarchy on Thursday, over lunch a few of us discussed how this could be enhanced in several ways. I think that the 'business' in the model can be considered analogous to human societies which have used different organizational structures to cope with differing dynamic environments, and perhaps have corresponding weakness or strengths in said environments. Many geographers/archaeologists consider the level of organizational complexity and inter-linkedness a key part of understanding the resilience and flexibility of a given society.

Some of the ways in which the model may be enhanced are:

# Encode more sophisticated adaptive strategies
# Add a cost of changing institutional structure, perhaps some sort of sunk-cost effect?
# Add more realistic dynamic environments

It is clear from historic human/environment interactions that some societies found it very hard to adapt to changing environmental conditions, and one possible explanation of this is that changing the structure of a society is non-linear process with thresholds, and for vulnerable societies crossing this threshold level was enough to cause collapse.

We could use historic case studies of failure (Norse Greenland, Easter Island) and success (Norse Iceland, many of the other pacific Islands, Japan) and ask, given we know the dynamics of the environment (though palo-environmental reconstruction) if the structure of the society had an impact on the success (or failure, i.e. mal-adaption) of that particular example.

[http://www.santafe.edu/events/workshops/index.php/Richard_Streeter Richard]

I'm interested: [http://www.santafe.edu/events/workshops/index.php/Steve_Hall Steve]

Me too. I'd like to hear about the cases: [http://www.santafe.edu/events/workshops/index.php/Catherine_Spence Cathy]

I can see some parallels between this and the classic tracking problem in control theory. I'd be interested. [[Srideep_Musuvathy|srideep]]

Antony and I have discussed a related problem. There are some recent results in biology relating the fitness cost of developing a sensor system to the entropy of a randomly varying environment. The dynamic environment in Josh's model could be generalized to such an entropy-parameterized environment, and one might expect a transition to the hierarchical structure (which is, more or less, a sensory system) as the entropy varies. [[Jacob_Foster|Jacob]]

===(Bayesian?) learning rates in biological and social systems===
Inspired by David Krakauer's lecture showing that evolution can be seen as a form of Bayesian learning, a question that naturally arises is how to measure learning rates in natural and artificial systems. In economics, [http://en.wikipedia.org/wiki/Experience_curve_effects learning curves and experience curves] are well-documented, typically following a power law shape. Can we quantify '''progress''' in biological, technological, and cultural evolution/development using this framework? Can we use '''efficiency''' as a universal measure? Also: what is the connection with the MEST-compression idea (Matter, Energy, Space, Time) of futurist [http://en.wikipedia.org/wiki/John_Smart_(futurist) John Smart]? (For example, think of future atomic neural nets mentioned by Alfred Hübler as a more compressed form of future intelligence than present state-of-the-art computing machines or brains).
Let me know if you'd like to brainstorm some of these ideas. [[B%C3%A9la_Nagy|Béla]]

=== An agent-based simulation of a pollination network===
Flowers need animals to visit them for reproduction, while these animals visit the flowers for food resources such as nectar. The pattern of interactions between flowers and insects can be thought of as a network of interactions. Different questions emerge in such network:

. What strategies flowers use in order to attract insects? What strategies insects use in order to visit the different flowers?

. What is the explanation for the specialization or the generalization of flowers and insects? why some flowers try to attrack a wide range of pollinators whereas other flowers specialize on a single species?

We would like to make an agent-based simulation based on an evolutionary game theory approach to try to find explanations for such questions and compare it with real data.

[[The pollination network wiki page]]

=== Structure Definitions===

At first sight, it seems obvious what a structure is. However, there are a
lot of different definitions of structure in use - in and between different
communities.

In the first meeting, I (Tanja) informed the others about my motivations for
looking at molecular structures based on RNA features: showing existing
definitions of RNA structure -- for example, minimum free energy, consensus
or abstract shapes, as well as discussing the importance of structure from a
phylogenetic viewpoint.

Moreover, we have had a short discussion about the ''Allegory of the Cave'' by Plato
and started discussing the following papers:

. Structure, Moshe Koppel, 1988

. Form and Content in Thinking Turing Machines, Oswald Wiener, 1988

Both in: The Universal Turing Machine / A Half Century Survey, edited R.
Herken, Springer-Verlag, New York.

We ended up with a lot of questions e.g. about TM, what is a sequence,
minimal descriptions, underlying structures, fundamental
structures, representatives, or the use of definitions in general - e.g
from a historical viewpoint, as well as to categorize them -- e.g. looking
at the purpose.

We already have different viewpoints in our group (e.g. architecture,
information theory, linguistics, logic, philosophy, computer science,
biology). At the last meeting, we decided to start a wiki page to play with
the different definitions between the fields and to prepare our next
meeting.

[[The structure definitions wiki page]]

We have already made an appointment for the second meeting:

9.00 on Wednesday, at Suite 3 (number 39 on the map), upper floor.

Somebody else, e.g from physics?

[[Tanja_Gesell|Tanja]]

I will bring what I can from physics.-- Craig

===Geometry of Fitness Landscapes===
As Dan mentioned today, the geometry of fitness landscapes is relatively unexplored terrain, with most of the underlying trait spaces being either simple (graph) or highly structured (Euclidean) . I've been interested in this topic for a while, so inspired by Dan's comment I thought I'd see if anyone else shared this interest. As a point of departure: there are some interesting articles in the Santa Fe volume on Evolutionary Dynamics, a paper by Stadler, Stadler, Wagner and Fontana (this latter regarding the underlying trait space), and some recent fancy work using computational algebraic geometry (which I don't understand entirely: http://www.biomedcentral.com/1471-2148/7/60/). As a related question, one might imagine exploring the "measurement theory" of fitness landscapes -- how do we reliably reconstruct the landscape geometry from finite measurements?

Anyone interested? (Sorry -- [[Jacob_Foster|Jacob]])

*I can't make out who posted this. I'd be willing to explore this a bit. I have some interested in algebraic topology, computational geometry stuff. However, it is not clear from the paper abstract what kind of 'computational algebraic geometry' they are talking about. [[Srideep_Musuvathy|srideep]]
*I might suggest looking at some of the work by Sergey Gavrilets as a stepping off point for some modern thought from biology on fitness landscapes. Poking around on the web to find a quick summary of some of his thoughts on Holey Adaptive landscapes I found this [http://www.cs.utk.edu/~langston/courses/cs594-fall2003/lecture27.html Lecture] he gave. It's long, but the end slides go into the meat and the begin provides a nice evolution of the ideas. [[Devin_Drown|Devin]]

On a related (but slightly less abstract) note, I am interested in modeling how interacting species co-construct their own and each other's fitness landscapes. I'm imagining an agent based model where each agent has "genes" which specify it's location in a fitness landscape, and also other genes which add some sort of random function to the landscape (as a very crude approximation, one could imagine using a mixture of Gaussians). As the species to evolve, you can watch how they move around in fitness space, and how they deform the landscape. This is an extremely rough idea, but I'd love to sit down and talk with some people about it. Maybe in a related discussion to one posted above.

Any takers? [[David_Foster|David]]
*So in populatoin genetics, I would call this coevolution between two or more players of an interaction (such as host-parasite, or plant and pollinator). Coevolution would occur "where the fitness of both species is affected by the distribution of traits in the other species." [http://dx.doi.org/10.1038/sj.hdy.6800949 (Gomulkiewicz et al 2007)]. I might sugggest looking into some of the coevolution theory literature from such authors as John Thompson, Richard Gomulkiewicz, Scott Nuismer, Sylvain Gandon and Curtis Lively. [[Devin_Drown|Devin]]

Something that came to my mind during the discussion of fitness landscapes was the idea of rate of adaptation to a dynamic fitness landscape. E.g. if the fitness landscape changes (e.g. climate) such that my current local maxima is now becoming a minima, how quickly must I explore the landscape to
esape extinction (dinosaurs seem to have failed this :-) Possibly interesting for both biological (antibiotic resistance, invasive species; climate change) and social systems (evolution of social systems in response to major technological change). Perhaps not enough data to do sensible work.

Any interest? [[Laura_Feeney | Laura]]
* I would say that invasive species provide a rich source of data on this subject as they can end up in an enviroment (and possibly a fitness landscape) that is quite different from their native range. A couple of competing ideas here is that invasives can have rather flat fitness functions with respect to their environment (lots of phenotypic plasticity) or perhaps have enought genetic variation such that an evolved response occurs in the new invaded range. There are of couse invasives that end up modifying the invaded range as well. [[Devin_Drown|Devin]]

== Working Groups ==
=== Summary of Modeling Tools ===
A few of us were talking about how helpful it would be to have a summary of the common and useful modeling tools annotated with their inherent assumptions, best practices, pitfalls, etc. At the moment, we thought we would create a wiki page with this information. Please [[Characterization of Modeling Tools|stop by]] and comment on your favorite tool. In the future, we may bring all interested folks together to discuss and try to come to a consensus.

=== Evolutionary Game Theory ===
A few of us were thinking that there wouldn't be enough time to discuss enough topics in EGT in a [[CSSS_2008_Santa_Fe-Tutorials#A_Crash_Course_to_Classical_and_Evolutionary_Game_Theory|single tutorial]], so I decided to post an offer for a working group that could meet fairly regularly to read and discuss papers from the field, suggest new topics, and possible projects. So far we've thought about looking at evolutionary branching models (in, say, a colony of yeast that produces an enzyme that can be shared by all individuals of the colony) and extending them from one population to two.

Please let me know if you'd be interested in joining. Feel free to add your name and topics you'd like to discuss. 
—-[[User:Jreyes|Josh]]

 Update! This has been scheduled on Friday from 3 - 5, location TBD.

*I'm interested! Actually, I know nothing about the topic, but I think that it could help me in my research. There is an interesting article about segregation and game theory [[Media:Zhang2004.pdf|(Zhang2004)]]. Maybe this could serve as inspiration for a project. (Flavia)
*I'm interested too. [[Kathleen_Sprouffske|Kathleen]]

=== Viral Modelling ===
I (Jeremie) propose to set up a workshop on viral modelling (biomathematics, epidemiology, virus kinetics, evolution, networks...). The idea would be that anyone could prepare a short and general introduction to its research area.
Please let me know if you'd be interested in joining. Feel free to add your name and topics you'd like to discuss.

This sound like fun. All of the above are of interest to me. Alex

I'm interested - Paul

Great idea. I might have some info on computer network virus propagation that I could contribute. - Justin

Ok, I suggest meeting on thursday from 4.30. Let's say we could prepare a 15-20 min tutorial, just to see if we are on the "same page". How does it sound ?

Please put me on any lists for such meetings or tutorials. I am very interested! I have studied quasispecies theory some, but I have no hands-on research experience in any of this. [[Molly_Rorick|Molly]]

=== Social (and other?) Networks ===

There are a number of people who are doing work with or related to social netwworks. Is there interest in a social networks working group? Alternatively, in a more general working group on networks and network based methods (biological, social, etc)?

Show interest and maybe times for a meeting below:

[[User:Laura_Feeney|Laura]] -- I'm free this evening; maybe tomorrow evening before tutorial
[[User:Jeremie Guedj|Jeremie]] -- I'm interested also; free tomorrow evening !

I'd also be interested in this. Tomorrow evening sounds good. [[User: Mark_Rivera | Mark]]

Tentatively scheduled for 7pm -- [[Laura_Feeney|Laura]]

Can we move at 6? I would like to attend Béla's tutorial ... [[User:Giovanni|Giovanni]]

=== Theory Group ===
'''Update (6/08/08):''' Ok, here's the link for [[Theory Group Texts]] page. Post any texts and links you find here so we've got a central clearing house. Some possibilities mentioned were Bruno Latour, Indian philosophy and complexity, etc. Also, '''next meeting''', Tuesday, lunchtime, one of dining hall side tables. So far on agenda - trying to get some of the major terms from the Delanda (strata/network, double articulation, Bwo, agent/operator, intercalary agent, etc.) and discuss further implications of diagram/abstract machine and hierarchy/meshwork distinction.

The general will has spoken and set a rough agenda for our joint exploration of the weird intersections between continental philosophy, critical theory, and complexity. We'll start by reading selections from Manuel De Landa's A Thousand Years of Nonlinear History -- Introduction, Sandstone and Granite, Species and Ecosystems, Arguments and Operators, Conclusions and Speculations. There are several copies floating around (if you have one could you please post here and if you need one do the same). We'll meet Sunday afternoon, to avoid conflict with the hike on Saturday, specific time to be determined.

Update! First meeting 4:20 - 6:00 on Sunday, at the coffee shop/lounge area.

We've discussed several next steps, which I'll post after dinner :)
--[[Jacob_Foster|Hypothetical Hypochondriac]]

- Possible topics we threw around for further discussion - basic working intro to and/or discussion of any of the following thinkers that have been linked to complexity studies - Gilles Deleuze (rhizomatics, diagram/complex assemblages, virtual multiplicities, non-binary theories of language, desiring machines, nomadism vs. state structures, capitalism and desiring-production, major/minor sciences/social groups, networked models of mind, time and duration, intuition as method), Jacques Lacan (matheme-ization of the freudian unconscious, subject/language, master signifiers and social discourse production, ties to topology), Alain Badiou (ethics of the event, ties to cantorian set theory, mathematical ontology), Michel Foucault(decentered subject, disiplinary institutions, biopower, shifting epistemes), C.S. Pierce (process semiotics), Whitehead (process metaphysics), etc. Any ideas/suggestions? (Chris)

Spoken like a true volunteer, Chris! I would very much like an introduction to Deleuze. Peirce and Whitehead would also be fantastic. I would further propose that with many of these thinkers (Deleuze, Lacan, Badiou) we can have some very interesting discussions of the use, misuse, and abuse of technical/mathematical/complexity metaphors outside of the home field (or -- is there even such a thing as abusing a metaphor?) . How can such translation best be achieved? Lacanian mathematics would be an especially interesting angle in my opinion.

Another possibility: Leibniz and the "pre-history" of complexity science! Maybe reading the Monadology, etc.

I believe Tanja will post a link to Krakauer's Metahistory article, to support a broad conversation about History, laws of History, the dangers of such laws, etc.

--[[Jacob_Foster|Hypothetical Hypochondriac]]

Hey All- Ok, found some public domain texts, will keep posting them to my profile page, so far including some Deleuze, Badiou, etc. Chris

Thanks, Chris!
I am looking forward for our discussions about Deleuze and De Landa and
I would very much like an introduction to Lacanian mathematics. Futhermore, I would
also be interested in discussing the Monadology of Leibniz.
As mentioned in the last meeting, it would be nice to take a look at the following paper: The Quest for Patterns in Metahistory, by [http://www.santafe.edu/~krakauer/Site/Reviews_%26_Articles.html. David Krakauer], SFI Bulletin. (2007). In addition, a link to the frescoes in the
[http://www.giottoagliscrovegni.it/eng/home.html Cappella Scrovegni] by Giotto, which I mentioned in the previous meeting.

--[[Tanja_Gesell|Tanja]]

One more link: http://www.netbase.org/delanda/meshwork.htm
MESHWORKS, HIERARCHIES AND INTERFACES

Craig

=== Non-equilibrium thermodynamics and the production of entropy ===
I brought with me the textbook [http://books.google.com/books?id=YRjfuEP_QycC&printsec=frontcover&dq=non-equilibrium+thermodynamics+and+the+production+of+entropy&ei=N19HSP-KCoHIigHFiczqBA&client=firefox-a&sig=sXSiqzPEHeNMOjPuyf986eR6Ljc "Non-equilibrium thermodynamics and the production of entropy" by Kleidon and Lorenz] and I have been trying to understand over the last 6 months what it is all about. The claim is that Nature, whatever in turbulence, life or either markets, tries to maximize the entropy *production*. As Stephen Guerin mentioned earlier this week in one of his lecture, entropy increases but when the system is sufficiently nonlinear, the entropy increases the most rapidly possible. Such overall principle enables to predict the evolution of the system. The book has several chapters showing where his principle could be used: turbulence, mean state of the atmosphere of Earth as well as other planets, the shaping of landscape by water, the coupled evolution of the biosphere and atmosphere, Gaia, economic processes, etc. As long as I do not understand where that principle comes from, I will stay skeptical of those claims. Still, if they are right, this can have important consequences in many fields. Go take a look at the book and if you are interested or if you know something about it, drop me a word. Chuss

[[Francois_Ascani|Francois]]

=== "Speculative" Neuroscience ===
Meet to discuss neuroscience problems and, ideally, cutting edge research. I have Kandel's reference text and Arbib's Handbook with me, and will bring them along for the ride and for background. Would also like to speculate on what's going on in your brain and mind :) Maybe we can meet this weekend sometime, or tonight (5/6) at SFI?

[[Nish_Aravamudan|Nish]]

Hi Nish, I'm interested (see also my notes above). I could meet early this evening, but otherwise I'll be away for the weekend. Please let me know a time for the evening. Otherwise, I'll set up a tutorial (aiming for a Wednesday AM time next week -- that work for you?) and see if there's interest among other folks. Cheers, [[User:Sayres|Sayres]] 14:41, 6 June 2008 (MDT)

I'd be interested in throwing my thoughts around. I am not sure if you are going to discuss ideas at a neuronal modeling and analysis level or the behaviour and organization of a network of neurons. [[Srideep_Musuvathy|srideep]]

I already went through most of the Kandell textbook during a reading group last year and I would like to discuss more some new stuff like mirror neurons which in that textbook were not present, as well the biochemical aspects of the brain, which we ashamelessly skipped since most of the people in the group were AI folks! [[User:Giovanni|Giovanni]]

Count me in! [[Christopher Vitale|Chris]]

== BrainStorming Projects ==

=== Peter ===

Emergence of language in an agent-based model
*I am still interested(Petr).

=== Giovanni ===

"Evolving" interactions in M.A.S. (See above my project ideas) [[User:Giovanni|Giovanni]]

=== Riley ===

Prediction in cultural markets

=== Abby ===

Misinformation

=== Antony ===

Time-horizon of political institutions for managing global environmental goods

=== Mark ===

Social network data/evolution of networks

=== Skyler ===

Networks plus application of biological methods

=== Qiqi ===

Public goods gam, group cooperation, social network

...> group behaviour of CSSS 2008 
gathering data from all of us, including game theory and perhaps agent based modeling 

=== Tanja ===

Structure definitions

=== Jon ===

- Epidemic models of depression/anxiety
- Inference of stochastic models

=== Rio ===

Social-ecological system -> Resilience institutions

=== Flávia ===

Emergence of segregation from a game theory perspective.

=== Francois ===

1) I have a time series of Chlorophyll a taken over 20 years. A Nature paper has claimed that a chaotic model reproduce the observed time series. Simple question: is there any evidence that the observed time series itself be chaotic? That would be a simple application of the Nonlinear Time Series Analysis introduced by Liz. May just be a nice exercise to do, not necessarily a final project. let me know if interesting in helping me.

2) Lattice-Botlzmann models are quite like the Agent-Based models but they seem better adapted to reproduce fluids in motion: the code is short and I have a couple of them that I got from open sources. I never used them but if anybody is interested to play with it, let me know. we could use the sand table that Redfish has and maybe reproduce some cool stuff such as the flooding of a valley, the breaking of a dam, or something like that!

3) what about the climate? nobody interested? this is one of the most *complex* system. we could try our hands on simple conceptual model of the climate?

[[Francois_Ascani|Francois]]

Hi, Francois. I'd be interested in helping with (1). Would love to speculate about (3), though I don't have much background. -[[Sarah_Cobey|Sarah]]

(1) Sounds interesting - The unAustralian Paul

I've had some experience in dealing with problems similar to (1). (3) is an interesting problem - we could play around with the lorenz equation or look at temperature data. I might be interested in in exploring the question as to whether 'global warming' can be reduced or if we were to try and reduce it, can we be certain that we do not over react! This is an interesting problem and I would like to get my feet wet in this sea of ideas. [[Srideep_Musuvathy|srideep]]

CSSS 2008 Santa Fe-Projects & Working Groups

2008-06-10T01:16:59Z

Drown: /* Geometry of Fitness Landscapes */

{{CSSS 2008 Santa Fe}}



== Potential Projects ==

=== Antagonistic interspecific interactions ===
After chatting with several people about host-parasite systems and hearing some of the comments at the icebreaker, I want to see if others are interested in potential projects in this area. As a way of getting some brain storming started, I’ve just typed up some topics (these include ideas I’ve heard from others here at Santa Fe) to see if there is critical mass and an interesting question.

Topics (no particular order)
'''Do we have one or two focal questions?'''
''Is there a desire to combine?''

#'''Impact of host heterogeneity (= consumer-resource dynamics with identity issues)''': ([[Sarah_Cobey|Sarah]] writes:) Most ecological models of consumer-resource interactions assume that all consumers "view" resources the same way, i.e., each resource has only one possible phenotype. For a host-pathogen system, this means that all hosts agree on which strains are identical and which are different, since all hosts are targeting the same antigenic sites (epitopes) of the pathogen in their immune response. When pathogen strains compete in this environment, a broad range of cool dynamics result ([http://www.scienceonline.org/cgi/content/abstract/280/5365/912 Gupta et al., Science, 1998]), depending on the strength of cross-immunity. There is evidence that hosts do not mount identical immune responses when challenged with the same strain of pathogen. In other words, a pathogen's phenotype is a function of the host. How does heterogeneity in hosts' immune responses--this multiplicity of phenotypes--affect competition among pathogens? These could be important results for the field. I'm thinking of doing some simple nonlinear dynamical analysis that builds on the framework in the Gupta paper. This problem seems broadly extensible to antagonistic interactions more generally, but I can't think of specific biological examples. Anyone interested? (Talk to me or post here!)
##Impact of immune system on host-parasite (/pathogen) interaction
##Seems like you could add some details of host genetics and then make up a matrix that describes the fitness dependences of the pathogens for each host genotype. -Devin
##Interesting paper by [http://www.pnas.org/cgi/content/abstract/104/18/7711 Recker et al (2008)] that could be interesting to discuss on this track as well. -Devin
###Can the Recker article be modified by including extra host compartment to represent different host genotypes?
###I'm not sure we need to add extra compartments, especially if we use a status-based approach with the ODEs. It would be worth talking about this problem in front of a blackboard. How about Thursday evening or Sunday? -[[Sarah_Cobey|Sarah]]
####<strike>Let's discuss 6pm Thursday</strike> completed
##Let's get some pictures of what this would this system would look like. I'll try and add something, but other's should drop in a pdf/powerpoint/artististic rendering
#'''Pathogen Modularity''' I would be interested in modeling whether some aspect of pathogen modularity-based evolvability (e.g. "reassortability" or reduced evolutionary constraints between epitopes) significantly affects the evolutionary success of the pathogen. I'd love to incorporate realistic-ish parameters to get a sense for whether this kind of evolvability has a ''significant'' effect on evolutionary success, and if so, whether this significant effect is large enough that we might expect second-order selection for pathogen evolvability. --[[Molly_Rorick|Molly]]
##Let's get some pictures of what this would this system would look like.
##This is very interesting. One could imagine using a (weighted?) network picture to capture the transitions. -- [[Jacob_Foster|Jacob]]
Right now we have a non-weighted network, but expanding the network to allow variation in edge weight will be a nice extension.--[[Molly_Rorick|Molly]]
#'''Need homes, or just ideas for later'''
##Effects of pathogen competition on epidemic outbreaks
##Spatial heterogeneity of transmission of parasites-- If we have time, I'd love to put the model we have started to develop on a graph or something...see the effects of spatial heterogeneity and the structure of the population on pathogen population, and maybe see how dynamics differ as one moves from an area of homogenous viral population to a "contact zone" where two strains compete...-[[Molly_Rorick|Molly]]
::*<strike>Infectious diseases: epidemic outbreaks vs. endemic steady states</strike>
::*<strike>Direct vs. vector transmission of parasites/pathogens</strike>
::*<strike>Non-genetic transmission of disease resistance</strike>

'''Interested?''' Please add ideas that you find interesting or would like to explore more (or just your name).

-[[Devin_Drown|Devin]]

I'm not at all a biologist, but perhaps there is some way to quantify modularlity in terms of clusters in these networks? Look at cluster dynamics? Clustering that takes into account link weights (e.g. greater link weight than expected by chance)? Perhaps some of this has been looked at? As in http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1865589 -- [[Laura_Feeney|Laura]]

Epidemiology in general. -[[Ruben_Kubiak|Ruben]]

=== Biological Levels / Phenotypes Discussion ===
We have a number of folks here either interested in or studying biology at various levels. I am interested in talking about ways in which it makes sense integrate different levels of biological knowledge into a representation of a system. For example, how might microRNA predictions be combined with gene expression networks (or proteomics or SNPs) to lead to a phenotype.

I am also interested in questions of how phenotypes are defined. Within an organ state (e.g., disease or not) for example, a phenotype might be defined as a gene expression pattern, a growth rate, a panel of microsatellite lengths, or functionally by in vivo or ex vivo capabilities to self-renew, etc. If what we are trying to understand is a larger question of disease or functionality, which phenotypes are interesting and useful (and possible!) to use?

I think these questions can be approached from a variety of ways. Off the top of my head, perhaps multi-scaled modeling or examining the system as a multi-level evolutionary system... I'm sure there are many others.

If you are interested, add your name and we can set up a time / place to talk about these and related questions. Also, please add anything you might want to include in a discussion!!

[[Kathleen_Sprouffske|Kathleen]]

=== Something in Neuroscience ===
I (Nish) would really like to do some more intensive, deep research in Neuroscience (Computational being my perspective). While I am fascinated by neurological and behavioral diseases, I would be open to any kind of neuroscientific problem. Anyone else?

Well, I guess that's my cue! I did my Ph.D. in Neuroscience, and I'd be glad to impart what knowledge I have. What I'd really be interested in is seeing what the interesting problems are which intersect neuroscience and complexity studies. It's surprising, given the obvious complexity of the nervous system, but not many of the articles I read really use this box of tools.

If other people express interest, I could organize a tutorial or small working group where I talk about some of the issues I know about in neuroscience and how they may relate to complexity. (One off the top of my head involves storing and retrieving memories, and is done by [http://www.molbio.princeton.edu/index.php?option=content&task=view&id=335 Carlos Brody] at Princeton; another possibility is applying Network Theory to functional connectivity using some new MRI-based data methods (including [http://en.wikipedia.org/wiki/Diffusion_tensor_imaging Diffusion Tensor Imaging])). But more generally, I think we could expand it to be a "speculative neuroscience" discussion, in which people throw crazy ideas at each other. [[User:Sayres|Sayres]] 18:34, 4 June 2008 (MDT)

- Sounds like fun to me. I think Gerald Edelman and Walter Freeman have done some work in this area, actually, but let's chat (Chris)

- Yeah, I know (some) of Freeman's stuff, but not Edelman's; I just looked him up online. This would be a good opportunity to catch up on some of these ideas. I was introduced to the Freeman ideas earlier, but he hasn't been doing much original research lately, and a lot of the attention is more on his collaborators, like Gyorgy Buszaki (sp?), whose work I would consider more focused on the trees than the forest. :) I myself have studied things at a slightly lower level than Freeman's big-picture ideas, but I think that's what this course is for. I will bring also some work I think is relevant in using forms of network theory to find clustering of objects (as well as in the olfactory system of insects, e.g. [http://laurentlab.caltech.edu/Welcome%20to%20the%20Laurent%20Lab.html Gilles Laurent]), and maybe talk about some newer models of decision making.

I see Nish has a little note below; I'll put some of my responses below there. I'll also go ahead and propose a small tutorial for next week; my plan would be to spend a little time presenting what I know, and encourage people to discuss their own interests. [[User:Sayres|Sayres]] 14:38, 6 June 2008 (MDT)

- yeah, wish I had my books from home here, my memory of Edelman's off the top of my head, but he's real good at synthesizing things (his 2001 book 'a universe of consciousness' is pretty damn good at that, once you get past the popsci intro chapters). Also worth checking out is Peter Gardenfors, and I really like Eric Baum's 'What is Thought?', which though based in computation rather than neurosci, is also great at bringing together so much new research. Terrence Deacon and Merlin Donald's stuff is also excellent, at least on how the evolution of the brain can shed light on these issues. But yeah, let's set up a time to chat on all this.

- This discussion about the storage of short term memory is very interesting. I am interested in finding more realistic models of decision making, e.g. how to model an exploratory process that may eventually lead to a decision? I'm mostly thinking at how to apply these ideas when doing agent based models of social systems. Broad ideas on the architecture of memory in the brain are definitively invaluable! Also, I'm very good at throwing crazy ideas on! Count me in! [[User:Giovanni|Giovanni]]

- Hey Giovanni, sounds good! If you're interested in decision-making, I'd like to direct you to the work of Greg Corrado, a friend and colleague of mine at Stanford. He's done work (with Leo Sugrue and Bill Newsome) on decision-making in tasks where the odds of a choice leading to a reward update dynamically. Here are links to a few of the papers:
* [http://www.jneurosci.org/cgi/content/abstract/27/31/8178 short review article outlining general approaches towards modeling decision-making in neuroscience: a good place to start]
* [http://www.ncbi.nlm.nih.gov/pubmed/15205529?ordinalpos=3&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum Science paper presenting the initial experiments on a simplified foraging task, and trying to understand neural correlates of perceived "value"]
* [http://www.ncbi.nlm.nih.gov/pubmed/16596981?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum theory paper explaining the "LNP" (linear-nonlinear-Poisson) model used to model decision-making processes]

I'll try to talk about this in the tuorial on Wednesday. But in case I don't have time to do it justice (likely), I think their model provides a nice compact description that does a very good job of explaining some complex data. Cheers, [[User:Sayres|Sayres]] 17:35, 9 June 2008 (MDT)

=== Evolving skepticism ===
I'd like to do anything relating to the introduction of misinformation into a system, but one concrete suggestion is looking at how one might evolve a skeptical response to defend against being "defrauded" (this could be in a social science or biological system).

Abby

=== if you can't grow '''Collapse''', you haven't explained it ===
Jared Diamond describes a five point framework for collapse of societies.
These points are:

-resilience of the environment to human caused damage

-climate change

-hostile neighbours

-friendly neighbours

-society's response to its problems

My proposal is to test these points in an agent based setup. we could for example use the parameter sweep etc.

If you are interested, add your name and we can set up a time / place to talk about these and related questions.

[http://www.santafe.edu/events/workshops/index.php/Dirk_van_Apeldoorn Dirk]

I am also very interested in this [http://www.santafe.edu/events/workshops/index.php/Richard_Streeter Richard]

Could we adapt this and include an urban perspective? [http://www.santafe.edu/events/workshops/index.php/Flavia_Feitosa Flávia]

Everybody needs his physicist. :-) - [[Ruben_Kubiak|Ruben]]

I'm interested in this project as well. [http://www.santafe.edu/events/workshops/index.php/Steve_Hall Steve]

I am interested!
[http://www.santafe.edu/events/workshops/index.php/John_Pang John]

Heck yeah! [[Rory_Sayres]] [[User:Sayres|Sayres]] 18:35, 4 June 2008 (MDT)

sounds fun. hope I can be of any help... [http://www.santafe.edu/events/workshops/index.php/Francois_Ascani Francois]

=== Let's make networks secure ===

I'm interested in making 'secure' networks with bound resources (like it is normal in reality). This is a very general questions and has many oppurtunities. For example:

- I have an epidemic and not enough vaccine - who should be vaccinated, who not?

- Terrorist try to smuggle a bomb into the land of Oz. Which flights between which airports should be especially watched to minimize this risk?

- How can we try to secure the internet with special anti-virus hubs? Is it possible to stop the epidemic of computer-viruses by special 'antibody' servers?

This just came to my mind and if anybody has other good ideas or wants to comment this - please feel free.

- [[Ruben_Kubiak|Ruben]]

- How to select nodes in the water system to detect the pollution efficiently?
- How to select individulas in the social network to let advertisement to spread efficiently?
- How to select blog to let people just see a small part of blog and get more information?
Data mining will be useful to analyize huge dataset. [see http://www.cs.cmu.edu/~jure/pubs/detect-kdd07.pdf]
-[[Jiang_Wu|Jiang]]

- Might be interested to see if all these problem can be generalized into a single combinatorial or asymptotic one. What kind of tools would you like to use? (I guess not agents :P) [[User:Giovanni|Giovanni]]

=== Network Security Concepts Inspired by Biological and Social Systems ===
Ruben – Was about to post this when I saw your entry. Sounds like we might have some overlap in our ideas…

One area that I am interested in for a project is applying concepts from biological and social systems to the area of computer network security. This is a broad topic and I am hoping to generate some discussion that might lead to a more well-defined research area.

In the biological area, for example, there have been recent developments in Artificial Immune Systems which borrow techniques from the immune system that enable virus detection and elimination in a self-organized and distributed manner. In particular, Stephanie Forest here at SFI has done work in this area. (see http://www.cs.unm.edu/~forrest/ , http://arxiv.org/ftp/arxiv/papers/0804/0804.1266.pdf) Other interesting research has been done by John Doyle at Caltech in which he compared the “robust yet fragile” organization structures of computer and biological networks (see pages 96-111 http://www.cds.caltech.edu/~doyle/GENSIPS/GENSIPS.pdf , http://www.cds.caltech.edu/~doyle/CmplxNets/)

In the social science area, I have been thinking about trust relationships and how they could apply to computer network security. Trust relationships are well established in computer networks for public key certificates. However, to my knowledge, there is no way to look at the “trust” of pieces of data in a network. Data is often scanned as it enters a network but is not tracked once it is inside to ensure that it behaves properly. This leaves many networks “hard on the outside, but soft and gooey on the inside.” One idea might be to leverage trust/reference concepts in social networks (e.g., eBay, citation networks, Amazon referrals, social websites, etc.) to construct a framework for “trusting” data throughout its lifetime in a network. For example, the more frequently that a piece of data is used effectively by an application might increase its trust. Also see http://www.mindswap.org/papers/Trust.pdf

Please list your name if you have any interest in this topic. Thanks.

Justin Darkoch

I'm happy to help look at this topic, but I suspect that for proper interdisciplinary work you need experts in biology, not computer systems... -- [[Laura_Feeney|Laura]]

=== Incorporating Data into Agent-Based Models ===
The rise of the "omics" fields of biology (e.g., DNA data in genomics, protein data in proteomics, etc) have resulted in a bewildering mass of data. I'm interested in exploring how these data can be incorporated into agent-based modeling strategies. Perhaps the data-mining folks have similar issues?

Perhaps this is a naive question and someone already knows about an instance where this has been successfully accomplished. If so, please forward it along to me!

In any case, I'd like to do anything from just talking about this problem to creating a simple agent-based model that uses publicly-available data. For example, a simple model of bacterial or yeast growth could be coupled with gene expression data from the cell cycle. I'd be very happy to explore any other systems folks are interested in as well.

[[Kathleen_Sprouffske|Kathleen]]

- I understand nothing about biology, but I'm always dealing with empirical data and the challenge of incorporating it to agent-based models. So, maybe we can talk a bit about it. ([http://www.santafe.edu/events/workshops/index.php/Flavia_Feitosa Flavia])

=== A Dance Evolution ===

I'm interested in trying to take Liz Bradly's alphabet dancer (that we saw Monday evening) and seeing if anything interesting/aesthetic could be done in a context where a set of such modeled dancers evolve their choice of movement (and perhaps their location/orientation) based on what their neighbors are doing.

My first thought was to evolve the selection of agent dance movements by analyzing how each selected movement (or perhaps simply their hand positions) temporally/spatially relate to the selected movements of its neighbors.

It might be an interesting context to explore self-organization and the role of conflict and cooperation in producing interesting emergent properties.

I'm thinking the primary work would be done in Netlogo. But I've noticed that Maya can be downloaded for a free 30 day trial period so the result could hopefully be visualized in 3D.

If you're interested leave your name below: [http://www.santafe.edu/events/workshops/index.php/Steve_Hall Steve]

One thing you might want to look at is looking at how dance notation (i.e. formal languages for describing choreograpy) could be used as a basis for "mutation", analogously to mutations on CAGT...
[[Laura_Feeney|Laura]]

=== Some ideas on modeling social media and on multi-agent modeling ===

([[User:Giovanni|Giovanni]]): With the term social media one can indicate the various web 2.0ish communities that are popping out on the internet these days. The following ideas come from watching Wikipedia's users community but I think there are correspondents in the other major social websites, as well on non-internet based communities (e.g. networks of scientific pubblications).
* '''Ownership of encyclopedic articles'''. Wikipedia's policy is that no one can claim ownership on a wiki entry. However, some forms of ownership are sometimes tolerated e.g. when an expert on a certain topic imposes his autority on non-expert editors. While it is generally wise to let the experts user to do this (since you want experts to collaborate to the project), sometimes this can lead to pathological cases in which the "owner" dictatorial methods discourage any other user to do any edit at all. This is a sorta of prisoner's dilemma, since you do not want the expert users to be banished by the community just, but at the same time you want to keep it as open as possible.
* '''Vandalism'''. Given a model in which agents either change the content of a page based on their point of view (these concepts have a precise definition) or revert it to a previous "clean" version, how can a community fight off vandal users? I would like to explore this problem with a "neutral"-like model e.g. in which the social phenomenon of vandalism is just explained in terms of "distance" from a point of view (again, these concepts do need and have a precise definition) and a "culture dependent" model, in which vandals form a population on their own and thus a "vandalic" cultural traits exist and is clearly identifiable by the agents.
* '''Community dynamics in terms of double selective pressure'''. This is a generalization of the previous two. These kind of problems suggest that there is a double selective mechanism by which users are "selected" into the community based on its current status (whatever this thing is), and at the same time the community's status is influenced by the users that live in it. A quick example: a Wikipedia plagued by too many vandals would probably discourage the average user to get in and fight vandalism, which makes life easier for vandals etc.

I would like to explore these problems either with multi-agent simulations or with differential equations. Data are usually not a problem if one wants to study social websites with open API.

On the other side of the MAS-coin, I'm also interested in general methodological problems of Multi-agent systems modeling.
* '''"Evolving" interactions in MAS'''. I talked briefly about that during the brainstorming session of Wednesday. I think some people were interested in that, so better to talk directly.
* '''Causality in MAS simulations and network motifs'''. Here the idea is to look at/develop algorithms to extract network motifs from multi-agent simulations. One has to use a model in which it is already clear what a causal relationship between two events is (I call these also interactions), or at least use the concept of "cause" used in graphical models. Other big question: once one has this kind information, how to use it?

I would be interested in pursuing this. There are some good ins'ights on how this was 'managed' in the development of Linux in Raymond's Cathedral and the Bazaar.
http://www.catb.org/~esr/writings/cathedral-bazaar/cathedral-bazaar/ Talks about that need for the 'inner circle'

Craig

what kind of questions do you want to solve using multi-agent model? Actually, I am really interested in the web2.0 and information diffusion pattern in this kind of web? When is the next meeting? Please add me in this discussion.
Jiangwu.john@gmail.com...[[Jiang_Wu|Jiang]]

=== Financial crisis in Housing Markets ===
After hearing the questions from Dan about market crashes, I got curious about a more recent market crisis, the housing market/home mortgage crunch. Over breakfast a few of us were discussing this and came up with a few questions.-[[Devin_Drown|Devin]]

'''Questions'''
#Is this really a complex system, or just something that is not transparent?
#What really caused our “crisis”?
#What happens if the “Fed” had let Bear Stearns go bankrupt?

'''Comments'''
*The crisis seems to be rooted in a separation between good information at the people who benefit from that information. (Abby)
*Can this be modeled in terms of banks with different risk behaviors/practices? (Devin)
*What about creating a simple ABM model with borrowers and lenders on Netlogo so we can play with heterogenous strategies from the perspective of the firm?(Carlos)
*We can introduce multiple lenders and introduce competition (or collusion?). (John)
*There should be accessible data on this. (John)
*Let's refine the idea. (John) ''see next section''

'''''Back of napkin'' model'''

{|
|-
! Borrow Agents
!
! Lender Agents
!
! Output
|-
|
*Risk profile (credit score)
*Desired loan
*Desired interest rate
| '''<--->'''
* Money
* Information
|
*Risk profile
*Capital constraint
*Interest optimum
*Underwriting rules
|
|
*Distribution of loans
*Default rate (distribution)
*Profits
*Partial equilibrium
*Time Horizon
|}

'''Interested folks'''
*[[Devin_Drown|Devin]]
*Abby
*[[cyepez|Carlos]]
*John Pang
* [[Rory_Sayres | Rory]]

- Hey, just some thoughts on this. Mark Taylor's work on micro/macro finance and crashes in light of complexity economics might be of interest here. He does a great job of explaining the LTCM/Asian tigers crash of 1999. David Harvey's work on the redistribution of crashes via international financial networks as ways of managing accumulation crises also has a lot to offer complexity economics. Eric Beinhocker's work also does a great job of laying out parameters of complexity economics as a whole. My concern about modeling these types of crashes is that modeling a given system can be really decieving, cause really there's an intricate web of complex nets at multiple levels of scale and widely spatially and contextually distributed, all in careful equilibrium, such that minor disturbances in one can trigger a phase change in another, making endogenous analysis problematic. Even the time series analysis done by Mandelbrot and co. in stock markets really does little more than a form of what Liz was doing with expanding 1D time-series of a 3D system, but with a LOT more degrees of freedom at stake. Which isn't to say this sort of modeling doesn't interest me, I just wonder how to do it justice. So, with the Bear Stearns crisis, it seems to me we've got another example of the financial industry coming up with new 'financial products' (in this case, sketchy loans) designed to avoid the fitness conditions provided via market regulation in congress. This leads, as it does everytime the financial sector outwits the regulators (as they do cyclically), to overleveraging of credit, inflation of the market, confidence crisis, government bailout of those who created the bubble, and large scale wealth transfer from low end of the market to the high end. Don't get me wrong, some lose their shirts on the high end, but overall, this sort of 'managed credit crisis' acts as an overall wealth pump from the low end to high end of the market, not due to conscious planning of the crisis on the part of the financiers, but as a macro effect of micro-rules based on outwitting regulators to maximize short range profits. Problem is, though, so many other networks are nested and intertwined here, I mean, how do you take into account shifts in the fitness environment leading to the evolution of new financial technologies, all of which caused the setup for the model in the first place? This problem REALLY interests me, just not sure how to do it in a way that doesn't ignore these complexities. Ideas? [[Christopher Vitale|Chris]]

'''Notes from the margin (6/8/08 - John)'''

We need to keep this fairly simple. We're not trying to model the US economy. Let's stay focused on what questions we're trying to answer.

Two types of agents: borrowers and lenders.

''Borrower''

A borrower agent is described by its credit score. A credit score is an weighted aggregate of the following four attributes of the borrower:

35% — punctuality of payment in the past (only includes payments later than 30 days past due)
30% — the amount of debt, expressed as the ratio of current revolving debt (credit card balances, etc.) to total available revolving credit (credit limits)
15% — length of credit history
10% — types of credit used (installment, revolving, consumer finance)
10% — recent search for credit and/or amount of credit obtained recently

Credit score distribution in the US is:

[[Image: scorerangepercentage.png]]

As a first-order approximation, this can give us the distribution of “risk” profile among borrower agents. Additionally, depending on income (and perhaps credit score itself), value of the property being considered is probably a variable – that is, amount of the loan (certainly, the maximum one can borrow is related to one’s credit score). For the purpose of our model, we should just assume adequate supply of homes fitting the borrower agent’s borrowing capacity. And given the interest rate (and for some people, monthly payment), the borrower agent will either go for the loan or not (and shop around).

We need to also determine an agent’s propensity to borrow – what motivates an agent to decide to purchase a home, and how do we model that?

''Lender''

When a lender agent receives an application for a mortgage, it will process the application according to some pre-specified underwriting rules.

Some good information on underwriting practices can be found at:

[http://en.wikipedia.org/wiki/Mortgage_underwriting_in_the_United_States Underwriting]

Information on subprime lending and subprime crisis can be found at:

[http://en.wikipedia.org/wiki/Subprime_lending Subprime]

We need to come up with a simple algorithm for the lender agent in the model, which will determine if the loan will be made, and if so, return principal amount of the loan and term structure of the loan (fixed or variable interest rate and length of loan – and if the rate is to vary, rules for that). What are the key variables we can tweak to either encourage or discourage non-prime lending?

''And after the loan, so what?''

Certain percent of the loans will default. How do we model this? For the first model, we can assume some percentage of default rate, given the borrower agent’s credit score (hopefully, this data is available). When do they default (first year? Second year?...)? Can we make some simplifying assumptions (e.g., if you don’t default during the first five years, you won’t default, or something like that) for the first model – we can refine the model after we get the first, simple model working.

''Future Refinements we can consider for the model''

Lender agent’s ability to continue lending should be dependent on previous periods default history (some can/should go bankrupt), which should be directly related to its profitability.

Borrower agents will shop around (quality index for lender agent, based on the quality of its portfolio, or perceived "easiness" of getting the loan).

===Dynamics systems applied in networks===
A year or so ago I discovered this researcher[http://www.anarg.jp/~leibnitz/research.php] who uses "Biologically-inspired attractor-selection" methods to route data through a network. It's been a while since I read it, but I believe the idea is to use systems of differential equations to solve networking problems such as finding robust, energy-efficient or shortest paths. I think it would be an interesting project to use both network and differential equations to derive some results, analytical, numerical and simulation. The network need not be a computer network.

Pessimistically, the approach might be just "bullsh*t and hype", but if so, we could analyse and suitably criticise it, and perhaps develop a better approach. Regardless, if anybody is interested, feel free to speak to me (my crap laptop broke recently so I won't be on the net as frequently as usual).

[[Holger Keeler|Paul]]

I think there are a few of us (notably Ruben and myself) that are interested broadly in bio-inspired network stuff (e.g., routing, virus spread, artificial immune systems, etc.) Perhaps we could try to consolidate our interests into a single project. Thoughts? - Justin

Perhaps work by Lidia Yamamoto would be of interest: http://cn.cs.unibas.ch/people/ly/ -- [[Laura_Feeney|Laura]]

I think Kenji Leibnitz' work in bio-routing is conceptually very intersesting, but not entirely convincing from a practical perspective. But I would be happy to meet with people to disucss and look for a project in in this area. [[Laura_Feeney|Laura]]

My computer works again, for the time being. I'm not too focus on biologically-inspired methods necessarily, though they are interesting. I thought this method would be interesting, but now I realise they're stochastic differential equations which don't lend themselves to analysis as easily, I believe. However, it may be possible to ignore the stochastic term. I will sleep on it. Paul

=== Evolving organizational flexibility in dynamic environments ===

Inspired by Josh's model of evolving organizational hierarchy on Thursday, over lunch a few of us discussed how this could be enhanced in several ways. I think that the 'business' in the model can be considered analogous to human societies which have used different organizational structures to cope with differing dynamic environments, and perhaps have corresponding weakness or strengths in said environments. Many geographers/archaeologists consider the level of organizational complexity and inter-linkedness a key part of understanding the resilience and flexibility of a given society.

Some of the ways in which the model may be enhanced are:

# Encode more sophisticated adaptive strategies
# Add a cost of changing institutional structure, perhaps some sort of sunk-cost effect?
# Add more realistic dynamic environments

It is clear from historic human/environment interactions that some societies found it very hard to adapt to changing environmental conditions, and one possible explanation of this is that changing the structure of a society is non-linear process with thresholds, and for vulnerable societies crossing this threshold level was enough to cause collapse.

We could use historic case studies of failure (Norse Greenland, Easter Island) and success (Norse Iceland, many of the other pacific Islands, Japan) and ask, given we know the dynamics of the environment (though palo-environmental reconstruction) if the structure of the society had an impact on the success (or failure, i.e. mal-adaption) of that particular example.

[http://www.santafe.edu/events/workshops/index.php/Richard_Streeter Richard]

I'm interested: [http://www.santafe.edu/events/workshops/index.php/Steve_Hall Steve]

Me too. I'd like to hear about the cases: [http://www.santafe.edu/events/workshops/index.php/Catherine_Spence Cathy]

I can see some parallels between this and the classic tracking problem in control theory. I'd be interested. [[Srideep_Musuvathy|srideep]]

Antony and I have discussed a related problem. There are some recent results in biology relating the fitness cost of developing a sensor system to the entropy of a randomly varying environment. The dynamic environment in Josh's model could be generalized to such an entropy-parameterized environment, and one might expect a transition to the hierarchical structure (which is, more or less, a sensory system) as the entropy varies. [[Jacob_Foster|Jacob]]

===(Bayesian?) learning rates in biological and social systems===
Inspired by David Krakauer's lecture showing that evolution can be seen as a form of Bayesian learning, a question that naturally arises is how to measure learning rates in natural and artificial systems. In economics, [http://en.wikipedia.org/wiki/Experience_curve_effects learning curves and experience curves] are well-documented, typically following a power law shape. Can we quantify '''progress''' in biological, technological, and cultural evolution/development using this framework? Can we use '''efficiency''' as a universal measure? Also: what is the connection with the MEST-compression idea (Matter, Energy, Space, Time) of futurist [http://en.wikipedia.org/wiki/John_Smart_(futurist) John Smart]? (For example, think of future atomic neural nets mentioned by Alfred Hübler as a more compressed form of future intelligence than present state-of-the-art computing machines or brains).
Let me know if you'd like to brainstorm some of these ideas. [[B%C3%A9la_Nagy|Béla]]

=== An agent-based simulation of a pollination network===
Flowers need animals to visit them for reproduction, while these animals visit the flowers for food resources such as nectar. The pattern of interactions between flowers and insects can be thought of as a network of interactions. Different questions emerge in such network:

. What strategies flowers use in order to attract insects? What strategies insects use in order to visit the different flowers?

. What is the explanation for the specialization or the generalization of flowers and insects? why some flowers try to attrack a wide range of pollinators whereas other flowers specialize on a single species?

We would like to make an agent-based simulation based on an evolutionary game theory approach to try to find explanations for such questions and compare it with real data.

[[The pollination network wiki page]]

=== Structure Definitions===

At first sight, it seems obvious what a structure is. However, there are a
lot of different definitions of structure in use - in and between different
communities.

In the first meeting, I (Tanja) informed the others about my motivations for
looking at molecular structures based on RNA features: showing existing
definitions of RNA structure -- for example, minimum free energy, consensus
or abstract shapes, as well as discussing the importance of structure from a
phylogenetic viewpoint.

Moreover, we have had a short discussion about the ''Allegory of the Cave'' by Plato
and started discussing the following papers:

. Structure, Moshe Koppel, 1988

. Form and Content in Thinking Turing Machines, Oswald Wiener, 1988

Both in: The Universal Turing Machine / A Half Century Survey, edited R.
Herken, Springer-Verlag, New York.

We ended up with a lot of questions e.g. about TM, what is a sequence,
minimal descriptions, underlying structures, fundamental
structures, representatives, or the use of definitions in general - e.g
from a historical viewpoint, as well as to categorize them -- e.g. looking
at the purpose.

We already have different viewpoints in our group (e.g. architecture,
information theory, linguistics, logic, philosophy, computer science,
biology). At the last meeting, we decided to start a wiki page to play with
the different definitions between the fields and to prepare our next
meeting.

[[The structure definitions wiki page]]

We have already made an appointment for the second meeting:

9.00 on Wednesday, at Suite 3 (number 39 on the map), upper floor.

Somebody else, e.g from physics?

[[Tanja_Gesell|Tanja]]

I will bring what I can from physics.-- Craig

===Geometry of Fitness Landscapes===
As Dan mentioned today, the geometry of fitness landscapes is relatively unexplored terrain, with most of the underlying trait spaces being either simple (graph) or highly structured (Euclidean) . I've been interested in this topic for a while, so inspired by Dan's comment I thought I'd see if anyone else shared this interest. As a point of departure: there are some interesting articles in the Santa Fe volume on Evolutionary Dynamics, a paper by Stadler, Stadler, Wagner and Fontana (this latter regarding the underlying trait space), and some recent fancy work using computational algebraic geometry (which I don't understand entirely: http://www.biomedcentral.com/1471-2148/7/60/). As a related question, one might imagine exploring the "measurement theory" of fitness landscapes -- how do we reliably reconstruct the landscape geometry from finite measurements?

Anyone interested? (Sorry -- [[Jacob_Foster|Jacob]])

*I can't make out who posted this. I'd be willing to explore this a bit. I have some interested in algebraic topology, computational geometry stuff. However, it is not clear from the paper abstract what kind of 'computational algebraic geometry' they are talking about. [[Srideep_Musuvathy|srideep]]
*I might suggest looking at some of the work by Sergey Gavrilets as a stepping off point for some modern thought from biology on fitness landscapes. Poking around on the web to find a quick summary of some of his thoughts on Holey Adaptive landscapes I found this [http://www.cs.utk.edu/~langston/courses/cs594-fall2003/lecture27.html Lecture] he gave. It's long, but the end slides go into the meat and the begin provides a nice evolution of the ideas. [[Devin_Drown|Devin]]

On a related (but slightly less abstract) note, I am interested in modeling how interacting species co-construct their own and each other's fitness landscapes. I'm imagining an agent based model where each agent has "genes" which specify it's location in a fitness landscape, and also other genes which add some sort of random function to the landscape (as a very crude approximation, one could imagine using a mixture of Gaussians). As the species to evolve, you can watch how they move around in fitness space, and how they deform the landscape. This is an extremely rough idea, but I'd love to sit down and talk with some people about it. Maybe in a related discussion to one posted above.

Any takers? [[David_Foster|David]]

Something that came to my mind during the discussion of fitness landscapes was the idea of rate of adaptation to a dynamic fitness landscape. E.g. if the fitness landscape changes (e.g. climate) such that my current local maxima is now becoming a minima, how quickly must I explore the landscape to
esape extinction (dinosaurs seem to have failed this :-) Possibly interesting for both biological (antibiotic resistance, invasive species; climate change) and social systems (evolution of social systems in response to major technological change). Perhaps not enough data to do sensible work.

Any interest? [[Laura_Feeney | Laura]]
* I would say that invasive species provide a rich source of data on this subject as they can end up in an enviroment (and possibly a fitness landscape) that is quite different from their native range. A couple of competing ideas here is that invasives can have rather flat fitness functions with respect to their environment (lots of phenotypic plasticity) or perhaps have enought genetic variation such that an evolved response occurs in the new invaded range. There are of couse invasives that end up modifying the invaded range as well. [[Devin_Drown|Devin]]

== Working Groups ==
=== Summary of Modeling Tools ===
A few of us were talking about how helpful it would be to have a summary of the common and useful modeling tools annotated with their inherent assumptions, best practices, pitfalls, etc. At the moment, we thought we would create a wiki page with this information. Please [[Characterization of Modeling Tools|stop by]] and comment on your favorite tool. In the future, we may bring all interested folks together to discuss and try to come to a consensus.

=== Evolutionary Game Theory ===
A few of us were thinking that there wouldn't be enough time to discuss enough topics in EGT in a [[CSSS_2008_Santa_Fe-Tutorials#A_Crash_Course_to_Classical_and_Evolutionary_Game_Theory|single tutorial]], so I decided to post an offer for a working group that could meet fairly regularly to read and discuss papers from the field, suggest new topics, and possible projects. So far we've thought about looking at evolutionary branching models (in, say, a colony of yeast that produces an enzyme that can be shared by all individuals of the colony) and extending them from one population to two.

Please let me know if you'd be interested in joining. Feel free to add your name and topics you'd like to discuss. 
—-[[User:Jreyes|Josh]]

 Update! This has been scheduled on Friday from 3 - 5, location TBD.

*I'm interested! Actually, I know nothing about the topic, but I think that it could help me in my research. There is an interesting article about segregation and game theory [[Media:Zhang2004.pdf|(Zhang2004)]]. Maybe this could serve as inspiration for a project. (Flavia)
*I'm interested too. [[Kathleen_Sprouffske|Kathleen]]

=== Viral Modelling ===
I (Jeremie) propose to set up a workshop on viral modelling (biomathematics, epidemiology, virus kinetics, evolution, networks...). The idea would be that anyone could prepare a short and general introduction to its research area.
Please let me know if you'd be interested in joining. Feel free to add your name and topics you'd like to discuss.

This sound like fun. All of the above are of interest to me. Alex

I'm interested - Paul

Great idea. I might have some info on computer network virus propagation that I could contribute. - Justin

Ok, I suggest meeting on thursday from 4.30. Let's say we could prepare a 15-20 min tutorial, just to see if we are on the "same page". How does it sound ?

Please put me on any lists for such meetings or tutorials. I am very interested! I have studied quasispecies theory some, but I have no hands-on research experience in any of this. [[Molly_Rorick|Molly]]

=== Social (and other?) Networks ===

There are a number of people who are doing work with or related to social netwworks. Is there interest in a social networks working group? Alternatively, in a more general working group on networks and network based methods (biological, social, etc)?

Show interest and maybe times for a meeting below:

[[User:Laura_Feeney|Laura]] -- I'm free this evening; maybe tomorrow evening before tutorial
[[User:Jeremie Guedj|Jeremie]] -- I'm interested also; free tomorrow evening !

I'd also be interested in this. Tomorrow evening sounds good. [[User: Mark_Rivera | Mark]]

Tentatively scheduled for 7pm -- [[Laura_Feeney|Laura]]

Can we move at 6? I would like to attend Béla's tutorial ... [[User:Giovanni|Giovanni]]

=== Theory Group ===
'''Update (6/08/08):''' Ok, here's the link for [[Theory Group Texts]] page. Post any texts and links you find here so we've got a central clearing house. Some possibilities mentioned were Bruno Latour, Indian philosophy and complexity, etc. Also, '''next meeting''', Tuesday, lunchtime, one of dining hall side tables. So far on agenda - trying to get some of the major terms from the Delanda (strata/network, double articulation, Bwo, agent/operator, intercalary agent, etc.) and discuss further implications of diagram/abstract machine and hierarchy/meshwork distinction.

The general will has spoken and set a rough agenda for our joint exploration of the weird intersections between continental philosophy, critical theory, and complexity. We'll start by reading selections from Manuel De Landa's A Thousand Years of Nonlinear History -- Introduction, Sandstone and Granite, Species and Ecosystems, Arguments and Operators, Conclusions and Speculations. There are several copies floating around (if you have one could you please post here and if you need one do the same). We'll meet Sunday afternoon, to avoid conflict with the hike on Saturday, specific time to be determined.

Update! First meeting 4:20 - 6:00 on Sunday, at the coffee shop/lounge area.

We've discussed several next steps, which I'll post after dinner :)
--[[Jacob_Foster|Hypothetical Hypochondriac]]

- Possible topics we threw around for further discussion - basic working intro to and/or discussion of any of the following thinkers that have been linked to complexity studies - Gilles Deleuze (rhizomatics, diagram/complex assemblages, virtual multiplicities, non-binary theories of language, desiring machines, nomadism vs. state structures, capitalism and desiring-production, major/minor sciences/social groups, networked models of mind, time and duration, intuition as method), Jacques Lacan (matheme-ization of the freudian unconscious, subject/language, master signifiers and social discourse production, ties to topology), Alain Badiou (ethics of the event, ties to cantorian set theory, mathematical ontology), Michel Foucault(decentered subject, disiplinary institutions, biopower, shifting epistemes), C.S. Pierce (process semiotics), Whitehead (process metaphysics), etc. Any ideas/suggestions? (Chris)

Spoken like a true volunteer, Chris! I would very much like an introduction to Deleuze. Peirce and Whitehead would also be fantastic. I would further propose that with many of these thinkers (Deleuze, Lacan, Badiou) we can have some very interesting discussions of the use, misuse, and abuse of technical/mathematical/complexity metaphors outside of the home field (or -- is there even such a thing as abusing a metaphor?) . How can such translation best be achieved? Lacanian mathematics would be an especially interesting angle in my opinion.

Another possibility: Leibniz and the "pre-history" of complexity science! Maybe reading the Monadology, etc.

I believe Tanja will post a link to Krakauer's Metahistory article, to support a broad conversation about History, laws of History, the dangers of such laws, etc.

--[[Jacob_Foster|Hypothetical Hypochondriac]]

Hey All- Ok, found some public domain texts, will keep posting them to my profile page, so far including some Deleuze, Badiou, etc. Chris

Thanks, Chris!
I am looking forward for our discussions about Deleuze and De Landa and
I would very much like an introduction to Lacanian mathematics. Futhermore, I would
also be interested in discussing the Monadology of Leibniz.
As mentioned in the last meeting, it would be nice to take a look at the following paper: The Quest for Patterns in Metahistory, by [http://www.santafe.edu/~krakauer/Site/Reviews_%26_Articles.html. David Krakauer], SFI Bulletin. (2007). In addition, a link to the frescoes in the
[http://www.giottoagliscrovegni.it/eng/home.html Cappella Scrovegni] by Giotto, which I mentioned in the previous meeting.

--[[Tanja_Gesell|Tanja]]

One more link: http://www.netbase.org/delanda/meshwork.htm
MESHWORKS, HIERARCHIES AND INTERFACES

Craig

=== Non-equilibrium thermodynamics and the production of entropy ===
I brought with me the textbook [http://books.google.com/books?id=YRjfuEP_QycC&printsec=frontcover&dq=non-equilibrium+thermodynamics+and+the+production+of+entropy&ei=N19HSP-KCoHIigHFiczqBA&client=firefox-a&sig=sXSiqzPEHeNMOjPuyf986eR6Ljc "Non-equilibrium thermodynamics and the production of entropy" by Kleidon and Lorenz] and I have been trying to understand over the last 6 months what it is all about. The claim is that Nature, whatever in turbulence, life or either markets, tries to maximize the entropy *production*. As Stephen Guerin mentioned earlier this week in one of his lecture, entropy increases but when the system is sufficiently nonlinear, the entropy increases the most rapidly possible. Such overall principle enables to predict the evolution of the system. The book has several chapters showing where his principle could be used: turbulence, mean state of the atmosphere of Earth as well as other planets, the shaping of landscape by water, the coupled evolution of the biosphere and atmosphere, Gaia, economic processes, etc. As long as I do not understand where that principle comes from, I will stay skeptical of those claims. Still, if they are right, this can have important consequences in many fields. Go take a look at the book and if you are interested or if you know something about it, drop me a word. Chuss

[[Francois_Ascani|Francois]]

=== "Speculative" Neuroscience ===
Meet to discuss neuroscience problems and, ideally, cutting edge research. I have Kandel's reference text and Arbib's Handbook with me, and will bring them along for the ride and for background. Would also like to speculate on what's going on in your brain and mind :) Maybe we can meet this weekend sometime, or tonight (5/6) at SFI?

[[Nish_Aravamudan|Nish]]

Hi Nish, I'm interested (see also my notes above). I could meet early this evening, but otherwise I'll be away for the weekend. Please let me know a time for the evening. Otherwise, I'll set up a tutorial (aiming for a Wednesday AM time next week -- that work for you?) and see if there's interest among other folks. Cheers, [[User:Sayres|Sayres]] 14:41, 6 June 2008 (MDT)

I'd be interested in throwing my thoughts around. I am not sure if you are going to discuss ideas at a neuronal modeling and analysis level or the behaviour and organization of a network of neurons. [[Srideep_Musuvathy|srideep]]

I already went through most of the Kandell textbook during a reading group last year and I would like to discuss more some new stuff like mirror neurons which in that textbook were not present, as well the biochemical aspects of the brain, which we ashamelessly skipped since most of the people in the group were AI folks! [[User:Giovanni|Giovanni]]

Count me in! [[Christopher Vitale|Chris]]

== BrainStorming Projects ==

=== Peter ===

Emergence of language in an agent-based model
*I am still interested(Petr).

=== Giovanni ===

"Evolving" interactions in M.A.S. (See above my project ideas) [[User:Giovanni|Giovanni]]

=== Riley ===

Prediction in cultural markets

=== Abby ===

Misinformation

=== Antony ===

Time-horizon of political institutions for managing global environmental goods

=== Mark ===

Social network data/evolution of networks

=== Skyler ===

Networks plus application of biological methods

=== Qiqi ===

Public goods gam, group cooperation, social network

...> group behaviour of CSSS 2008 
gathering data from all of us, including game theory and perhaps agent based modeling 

=== Tanja ===

Structure definitions

=== Jon ===

- Epidemic models of depression/anxiety
- Inference of stochastic models

=== Rio ===

Social-ecological system -> Resilience institutions

=== Flávia ===

Emergence of segregation from a game theory perspective.

=== Francois ===

1) I have a time series of Chlorophyll a taken over 20 years. A Nature paper has claimed that a chaotic model reproduce the observed time series. Simple question: is there any evidence that the observed time series itself be chaotic? That would be a simple application of the Nonlinear Time Series Analysis introduced by Liz. May just be a nice exercise to do, not necessarily a final project. let me know if interesting in helping me.

2) Lattice-Botlzmann models are quite like the Agent-Based models but they seem better adapted to reproduce fluids in motion: the code is short and I have a couple of them that I got from open sources. I never used them but if anybody is interested to play with it, let me know. we could use the sand table that Redfish has and maybe reproduce some cool stuff such as the flooding of a valley, the breaking of a dam, or something like that!

3) what about the climate? nobody interested? this is one of the most *complex* system. we could try our hands on simple conceptual model of the climate?

[[Francois_Ascani|Francois]]

Hi, Francois. I'd be interested in helping with (1). Would love to speculate about (3), though I don't have much background. -[[Sarah_Cobey|Sarah]]

(1) Sounds interesting - The unAustralian Paul

I've had some experience in dealing with problems similar to (1). (3) is an interesting problem - we could play around with the lorenz equation or look at temperature data. I might be interested in in exploring the question as to whether 'global warming' can be reduced or if we were to try and reduce it, can we be certain that we do not over react! This is an interesting problem and I would like to get my feet wet in this sea of ideas. [[Srideep_Musuvathy|srideep]]

CSSS 2008 Santa Fe-Projects & Working Groups

2008-06-10T01:09:27Z

Drown: /* Geometry of Fitness Landscapes */

{{CSSS 2008 Santa Fe}}



== Potential Projects ==

=== Antagonistic interspecific interactions ===
After chatting with several people about host-parasite systems and hearing some of the comments at the icebreaker, I want to see if others are interested in potential projects in this area. As a way of getting some brain storming started, I’ve just typed up some topics (these include ideas I’ve heard from others here at Santa Fe) to see if there is critical mass and an interesting question.

Topics (no particular order)
'''Do we have one or two focal questions?'''
''Is there a desire to combine?''

#'''Impact of host heterogeneity (= consumer-resource dynamics with identity issues)''': ([[Sarah_Cobey|Sarah]] writes:) Most ecological models of consumer-resource interactions assume that all consumers "view" resources the same way, i.e., each resource has only one possible phenotype. For a host-pathogen system, this means that all hosts agree on which strains are identical and which are different, since all hosts are targeting the same antigenic sites (epitopes) of the pathogen in their immune response. When pathogen strains compete in this environment, a broad range of cool dynamics result ([http://www.scienceonline.org/cgi/content/abstract/280/5365/912 Gupta et al., Science, 1998]), depending on the strength of cross-immunity. There is evidence that hosts do not mount identical immune responses when challenged with the same strain of pathogen. In other words, a pathogen's phenotype is a function of the host. How does heterogeneity in hosts' immune responses--this multiplicity of phenotypes--affect competition among pathogens? These could be important results for the field. I'm thinking of doing some simple nonlinear dynamical analysis that builds on the framework in the Gupta paper. This problem seems broadly extensible to antagonistic interactions more generally, but I can't think of specific biological examples. Anyone interested? (Talk to me or post here!)
##Impact of immune system on host-parasite (/pathogen) interaction
##Seems like you could add some details of host genetics and then make up a matrix that describes the fitness dependences of the pathogens for each host genotype. -Devin
##Interesting paper by [http://www.pnas.org/cgi/content/abstract/104/18/7711 Recker et al (2008)] that could be interesting to discuss on this track as well. -Devin
###Can the Recker article be modified by including extra host compartment to represent different host genotypes?
###I'm not sure we need to add extra compartments, especially if we use a status-based approach with the ODEs. It would be worth talking about this problem in front of a blackboard. How about Thursday evening or Sunday? -[[Sarah_Cobey|Sarah]]
####<strike>Let's discuss 6pm Thursday</strike> completed
##Let's get some pictures of what this would this system would look like. I'll try and add something, but other's should drop in a pdf/powerpoint/artististic rendering
#'''Pathogen Modularity''' I would be interested in modeling whether some aspect of pathogen modularity-based evolvability (e.g. "reassortability" or reduced evolutionary constraints between epitopes) significantly affects the evolutionary success of the pathogen. I'd love to incorporate realistic-ish parameters to get a sense for whether this kind of evolvability has a ''significant'' effect on evolutionary success, and if so, whether this significant effect is large enough that we might expect second-order selection for pathogen evolvability. --[[Molly_Rorick|Molly]]
##Let's get some pictures of what this would this system would look like.
##This is very interesting. One could imagine using a (weighted?) network picture to capture the transitions. -- [[Jacob_Foster|Jacob]]
Right now we have a non-weighted network, but expanding the network to allow variation in edge weight will be a nice extension.--[[Molly_Rorick|Molly]]
#'''Need homes, or just ideas for later'''
##Effects of pathogen competition on epidemic outbreaks
##Spatial heterogeneity of transmission of parasites-- If we have time, I'd love to put the model we have started to develop on a graph or something...see the effects of spatial heterogeneity and the structure of the population on pathogen population, and maybe see how dynamics differ as one moves from an area of homogenous viral population to a "contact zone" where two strains compete...-[[Molly_Rorick|Molly]]
::*<strike>Infectious diseases: epidemic outbreaks vs. endemic steady states</strike>
::*<strike>Direct vs. vector transmission of parasites/pathogens</strike>
::*<strike>Non-genetic transmission of disease resistance</strike>

'''Interested?''' Please add ideas that you find interesting or would like to explore more (or just your name).

-[[Devin_Drown|Devin]]

I'm not at all a biologist, but perhaps there is some way to quantify modularlity in terms of clusters in these networks? Look at cluster dynamics? Clustering that takes into account link weights (e.g. greater link weight than expected by chance)? Perhaps some of this has been looked at? As in http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1865589 -- [[Laura_Feeney|Laura]]

Epidemiology in general. -[[Ruben_Kubiak|Ruben]]

=== Biological Levels / Phenotypes Discussion ===
We have a number of folks here either interested in or studying biology at various levels. I am interested in talking about ways in which it makes sense integrate different levels of biological knowledge into a representation of a system. For example, how might microRNA predictions be combined with gene expression networks (or proteomics or SNPs) to lead to a phenotype.

I am also interested in questions of how phenotypes are defined. Within an organ state (e.g., disease or not) for example, a phenotype might be defined as a gene expression pattern, a growth rate, a panel of microsatellite lengths, or functionally by in vivo or ex vivo capabilities to self-renew, etc. If what we are trying to understand is a larger question of disease or functionality, which phenotypes are interesting and useful (and possible!) to use?

I think these questions can be approached from a variety of ways. Off the top of my head, perhaps multi-scaled modeling or examining the system as a multi-level evolutionary system... I'm sure there are many others.

If you are interested, add your name and we can set up a time / place to talk about these and related questions. Also, please add anything you might want to include in a discussion!!

[[Kathleen_Sprouffske|Kathleen]]

=== Something in Neuroscience ===
I (Nish) would really like to do some more intensive, deep research in Neuroscience (Computational being my perspective). While I am fascinated by neurological and behavioral diseases, I would be open to any kind of neuroscientific problem. Anyone else?

Well, I guess that's my cue! I did my Ph.D. in Neuroscience, and I'd be glad to impart what knowledge I have. What I'd really be interested in is seeing what the interesting problems are which intersect neuroscience and complexity studies. It's surprising, given the obvious complexity of the nervous system, but not many of the articles I read really use this box of tools.

If other people express interest, I could organize a tutorial or small working group where I talk about some of the issues I know about in neuroscience and how they may relate to complexity. (One off the top of my head involves storing and retrieving memories, and is done by [http://www.molbio.princeton.edu/index.php?option=content&task=view&id=335 Carlos Brody] at Princeton; another possibility is applying Network Theory to functional connectivity using some new MRI-based data methods (including [http://en.wikipedia.org/wiki/Diffusion_tensor_imaging Diffusion Tensor Imaging])). But more generally, I think we could expand it to be a "speculative neuroscience" discussion, in which people throw crazy ideas at each other. [[User:Sayres|Sayres]] 18:34, 4 June 2008 (MDT)

- Sounds like fun to me. I think Gerald Edelman and Walter Freeman have done some work in this area, actually, but let's chat (Chris)

- Yeah, I know (some) of Freeman's stuff, but not Edelman's; I just looked him up online. This would be a good opportunity to catch up on some of these ideas. I was introduced to the Freeman ideas earlier, but he hasn't been doing much original research lately, and a lot of the attention is more on his collaborators, like Gyorgy Buszaki (sp?), whose work I would consider more focused on the trees than the forest. :) I myself have studied things at a slightly lower level than Freeman's big-picture ideas, but I think that's what this course is for. I will bring also some work I think is relevant in using forms of network theory to find clustering of objects (as well as in the olfactory system of insects, e.g. [http://laurentlab.caltech.edu/Welcome%20to%20the%20Laurent%20Lab.html Gilles Laurent]), and maybe talk about some newer models of decision making.

I see Nish has a little note below; I'll put some of my responses below there. I'll also go ahead and propose a small tutorial for next week; my plan would be to spend a little time presenting what I know, and encourage people to discuss their own interests. [[User:Sayres|Sayres]] 14:38, 6 June 2008 (MDT)

- yeah, wish I had my books from home here, my memory of Edelman's off the top of my head, but he's real good at synthesizing things (his 2001 book 'a universe of consciousness' is pretty damn good at that, once you get past the popsci intro chapters). Also worth checking out is Peter Gardenfors, and I really like Eric Baum's 'What is Thought?', which though based in computation rather than neurosci, is also great at bringing together so much new research. Terrence Deacon and Merlin Donald's stuff is also excellent, at least on how the evolution of the brain can shed light on these issues. But yeah, let's set up a time to chat on all this.

- This discussion about the storage of short term memory is very interesting. I am interested in finding more realistic models of decision making, e.g. how to model an exploratory process that may eventually lead to a decision? I'm mostly thinking at how to apply these ideas when doing agent based models of social systems. Broad ideas on the architecture of memory in the brain are definitively invaluable! Also, I'm very good at throwing crazy ideas on! Count me in! [[User:Giovanni|Giovanni]]

- Hey Giovanni, sounds good! If you're interested in decision-making, I'd like to direct you to the work of Greg Corrado, a friend and colleague of mine at Stanford. He's done work (with Leo Sugrue and Bill Newsome) on decision-making in tasks where the odds of a choice leading to a reward update dynamically. Here are links to a few of the papers:
* [http://www.jneurosci.org/cgi/content/abstract/27/31/8178 short review article outlining general approaches towards modeling decision-making in neuroscience: a good place to start]
* [http://www.ncbi.nlm.nih.gov/pubmed/15205529?ordinalpos=3&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum Science paper presenting the initial experiments on a simplified foraging task, and trying to understand neural correlates of perceived "value"]
* [http://www.ncbi.nlm.nih.gov/pubmed/16596981?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum theory paper explaining the "LNP" (linear-nonlinear-Poisson) model used to model decision-making processes]

I'll try to talk about this in the tuorial on Wednesday. But in case I don't have time to do it justice (likely), I think their model provides a nice compact description that does a very good job of explaining some complex data. Cheers, [[User:Sayres|Sayres]] 17:35, 9 June 2008 (MDT)

=== Evolving skepticism ===
I'd like to do anything relating to the introduction of misinformation into a system, but one concrete suggestion is looking at how one might evolve a skeptical response to defend against being "defrauded" (this could be in a social science or biological system).

Abby

=== if you can't grow '''Collapse''', you haven't explained it ===
Jared Diamond describes a five point framework for collapse of societies.
These points are:

-resilience of the environment to human caused damage

-climate change

-hostile neighbours

-friendly neighbours

-society's response to its problems

My proposal is to test these points in an agent based setup. we could for example use the parameter sweep etc.

If you are interested, add your name and we can set up a time / place to talk about these and related questions.

[http://www.santafe.edu/events/workshops/index.php/Dirk_van_Apeldoorn Dirk]

I am also very interested in this [http://www.santafe.edu/events/workshops/index.php/Richard_Streeter Richard]

Could we adapt this and include an urban perspective? [http://www.santafe.edu/events/workshops/index.php/Flavia_Feitosa Flávia]

Everybody needs his physicist. :-) - [[Ruben_Kubiak|Ruben]]

I'm interested in this project as well. [http://www.santafe.edu/events/workshops/index.php/Steve_Hall Steve]

I am interested!
[http://www.santafe.edu/events/workshops/index.php/John_Pang John]

Heck yeah! [[Rory_Sayres]] [[User:Sayres|Sayres]] 18:35, 4 June 2008 (MDT)

sounds fun. hope I can be of any help... [http://www.santafe.edu/events/workshops/index.php/Francois_Ascani Francois]

=== Let's make networks secure ===

I'm interested in making 'secure' networks with bound resources (like it is normal in reality). This is a very general questions and has many oppurtunities. For example:

- I have an epidemic and not enough vaccine - who should be vaccinated, who not?

- Terrorist try to smuggle a bomb into the land of Oz. Which flights between which airports should be especially watched to minimize this risk?

- How can we try to secure the internet with special anti-virus hubs? Is it possible to stop the epidemic of computer-viruses by special 'antibody' servers?

This just came to my mind and if anybody has other good ideas or wants to comment this - please feel free.

- [[Ruben_Kubiak|Ruben]]

- How to select nodes in the water system to detect the pollution efficiently?
- How to select individulas in the social network to let advertisement to spread efficiently?
- How to select blog to let people just see a small part of blog and get more information?
Data mining will be useful to analyize huge dataset. [see http://www.cs.cmu.edu/~jure/pubs/detect-kdd07.pdf]
-[[Jiang_Wu|Jiang]]

- Might be interested to see if all these problem can be generalized into a single combinatorial or asymptotic one. What kind of tools would you like to use? (I guess not agents :P) [[User:Giovanni|Giovanni]]

=== Network Security Concepts Inspired by Biological and Social Systems ===
Ruben – Was about to post this when I saw your entry. Sounds like we might have some overlap in our ideas…

One area that I am interested in for a project is applying concepts from biological and social systems to the area of computer network security. This is a broad topic and I am hoping to generate some discussion that might lead to a more well-defined research area.

In the biological area, for example, there have been recent developments in Artificial Immune Systems which borrow techniques from the immune system that enable virus detection and elimination in a self-organized and distributed manner. In particular, Stephanie Forest here at SFI has done work in this area. (see http://www.cs.unm.edu/~forrest/ , http://arxiv.org/ftp/arxiv/papers/0804/0804.1266.pdf) Other interesting research has been done by John Doyle at Caltech in which he compared the “robust yet fragile” organization structures of computer and biological networks (see pages 96-111 http://www.cds.caltech.edu/~doyle/GENSIPS/GENSIPS.pdf , http://www.cds.caltech.edu/~doyle/CmplxNets/)

In the social science area, I have been thinking about trust relationships and how they could apply to computer network security. Trust relationships are well established in computer networks for public key certificates. However, to my knowledge, there is no way to look at the “trust” of pieces of data in a network. Data is often scanned as it enters a network but is not tracked once it is inside to ensure that it behaves properly. This leaves many networks “hard on the outside, but soft and gooey on the inside.” One idea might be to leverage trust/reference concepts in social networks (e.g., eBay, citation networks, Amazon referrals, social websites, etc.) to construct a framework for “trusting” data throughout its lifetime in a network. For example, the more frequently that a piece of data is used effectively by an application might increase its trust. Also see http://www.mindswap.org/papers/Trust.pdf

Please list your name if you have any interest in this topic. Thanks.

Justin Darkoch

I'm happy to help look at this topic, but I suspect that for proper interdisciplinary work you need experts in biology, not computer systems... -- [[Laura_Feeney|Laura]]

=== Incorporating Data into Agent-Based Models ===
The rise of the "omics" fields of biology (e.g., DNA data in genomics, protein data in proteomics, etc) have resulted in a bewildering mass of data. I'm interested in exploring how these data can be incorporated into agent-based modeling strategies. Perhaps the data-mining folks have similar issues?

Perhaps this is a naive question and someone already knows about an instance where this has been successfully accomplished. If so, please forward it along to me!

In any case, I'd like to do anything from just talking about this problem to creating a simple agent-based model that uses publicly-available data. For example, a simple model of bacterial or yeast growth could be coupled with gene expression data from the cell cycle. I'd be very happy to explore any other systems folks are interested in as well.

[[Kathleen_Sprouffske|Kathleen]]

- I understand nothing about biology, but I'm always dealing with empirical data and the challenge of incorporating it to agent-based models. So, maybe we can talk a bit about it. ([http://www.santafe.edu/events/workshops/index.php/Flavia_Feitosa Flavia])

=== A Dance Evolution ===

I'm interested in trying to take Liz Bradly's alphabet dancer (that we saw Monday evening) and seeing if anything interesting/aesthetic could be done in a context where a set of such modeled dancers evolve their choice of movement (and perhaps their location/orientation) based on what their neighbors are doing.

My first thought was to evolve the selection of agent dance movements by analyzing how each selected movement (or perhaps simply their hand positions) temporally/spatially relate to the selected movements of its neighbors.

It might be an interesting context to explore self-organization and the role of conflict and cooperation in producing interesting emergent properties.

I'm thinking the primary work would be done in Netlogo. But I've noticed that Maya can be downloaded for a free 30 day trial period so the result could hopefully be visualized in 3D.

If you're interested leave your name below: [http://www.santafe.edu/events/workshops/index.php/Steve_Hall Steve]

One thing you might want to look at is looking at how dance notation (i.e. formal languages for describing choreograpy) could be used as a basis for "mutation", analogously to mutations on CAGT...
[[Laura_Feeney|Laura]]

=== Some ideas on modeling social media and on multi-agent modeling ===

([[User:Giovanni|Giovanni]]): With the term social media one can indicate the various web 2.0ish communities that are popping out on the internet these days. The following ideas come from watching Wikipedia's users community but I think there are correspondents in the other major social websites, as well on non-internet based communities (e.g. networks of scientific pubblications).
* '''Ownership of encyclopedic articles'''. Wikipedia's policy is that no one can claim ownership on a wiki entry. However, some forms of ownership are sometimes tolerated e.g. when an expert on a certain topic imposes his autority on non-expert editors. While it is generally wise to let the experts user to do this (since you want experts to collaborate to the project), sometimes this can lead to pathological cases in which the "owner" dictatorial methods discourage any other user to do any edit at all. This is a sorta of prisoner's dilemma, since you do not want the expert users to be banished by the community just, but at the same time you want to keep it as open as possible.
* '''Vandalism'''. Given a model in which agents either change the content of a page based on their point of view (these concepts have a precise definition) or revert it to a previous "clean" version, how can a community fight off vandal users? I would like to explore this problem with a "neutral"-like model e.g. in which the social phenomenon of vandalism is just explained in terms of "distance" from a point of view (again, these concepts do need and have a precise definition) and a "culture dependent" model, in which vandals form a population on their own and thus a "vandalic" cultural traits exist and is clearly identifiable by the agents.
* '''Community dynamics in terms of double selective pressure'''. This is a generalization of the previous two. These kind of problems suggest that there is a double selective mechanism by which users are "selected" into the community based on its current status (whatever this thing is), and at the same time the community's status is influenced by the users that live in it. A quick example: a Wikipedia plagued by too many vandals would probably discourage the average user to get in and fight vandalism, which makes life easier for vandals etc.

I would like to explore these problems either with multi-agent simulations or with differential equations. Data are usually not a problem if one wants to study social websites with open API.

On the other side of the MAS-coin, I'm also interested in general methodological problems of Multi-agent systems modeling.
* '''"Evolving" interactions in MAS'''. I talked briefly about that during the brainstorming session of Wednesday. I think some people were interested in that, so better to talk directly.
* '''Causality in MAS simulations and network motifs'''. Here the idea is to look at/develop algorithms to extract network motifs from multi-agent simulations. One has to use a model in which it is already clear what a causal relationship between two events is (I call these also interactions), or at least use the concept of "cause" used in graphical models. Other big question: once one has this kind information, how to use it?

I would be interested in pursuing this. There are some good ins'ights on how this was 'managed' in the development of Linux in Raymond's Cathedral and the Bazaar.
http://www.catb.org/~esr/writings/cathedral-bazaar/cathedral-bazaar/ Talks about that need for the 'inner circle'

Craig

what kind of questions do you want to solve using multi-agent model? Actually, I am really interested in the web2.0 and information diffusion pattern in this kind of web? When is the next meeting? Please add me in this discussion.
Jiangwu.john@gmail.com...[[Jiang_Wu|Jiang]]

=== Financial crisis in Housing Markets ===
After hearing the questions from Dan about market crashes, I got curious about a more recent market crisis, the housing market/home mortgage crunch. Over breakfast a few of us were discussing this and came up with a few questions.-[[Devin_Drown|Devin]]

'''Questions'''
#Is this really a complex system, or just something that is not transparent?
#What really caused our “crisis”?
#What happens if the “Fed” had let Bear Stearns go bankrupt?

'''Comments'''
*The crisis seems to be rooted in a separation between good information at the people who benefit from that information. (Abby)
*Can this be modeled in terms of banks with different risk behaviors/practices? (Devin)
*What about creating a simple ABM model with borrowers and lenders on Netlogo so we can play with heterogenous strategies from the perspective of the firm?(Carlos)
*We can introduce multiple lenders and introduce competition (or collusion?). (John)
*There should be accessible data on this. (John)
*Let's refine the idea. (John) ''see next section''

'''''Back of napkin'' model'''

{|
|-
! Borrow Agents
!
! Lender Agents
!
! Output
|-
|
*Risk profile (credit score)
*Desired loan
*Desired interest rate
| '''<--->'''
* Money
* Information
|
*Risk profile
*Capital constraint
*Interest optimum
*Underwriting rules
|
|
*Distribution of loans
*Default rate (distribution)
*Profits
*Partial equilibrium
*Time Horizon
|}

'''Interested folks'''
*[[Devin_Drown|Devin]]
*Abby
*[[cyepez|Carlos]]
*John Pang
* [[Rory_Sayres | Rory]]

- Hey, just some thoughts on this. Mark Taylor's work on micro/macro finance and crashes in light of complexity economics might be of interest here. He does a great job of explaining the LTCM/Asian tigers crash of 1999. David Harvey's work on the redistribution of crashes via international financial networks as ways of managing accumulation crises also has a lot to offer complexity economics. Eric Beinhocker's work also does a great job of laying out parameters of complexity economics as a whole. My concern about modeling these types of crashes is that modeling a given system can be really decieving, cause really there's an intricate web of complex nets at multiple levels of scale and widely spatially and contextually distributed, all in careful equilibrium, such that minor disturbances in one can trigger a phase change in another, making endogenous analysis problematic. Even the time series analysis done by Mandelbrot and co. in stock markets really does little more than a form of what Liz was doing with expanding 1D time-series of a 3D system, but with a LOT more degrees of freedom at stake. Which isn't to say this sort of modeling doesn't interest me, I just wonder how to do it justice. So, with the Bear Stearns crisis, it seems to me we've got another example of the financial industry coming up with new 'financial products' (in this case, sketchy loans) designed to avoid the fitness conditions provided via market regulation in congress. This leads, as it does everytime the financial sector outwits the regulators (as they do cyclically), to overleveraging of credit, inflation of the market, confidence crisis, government bailout of those who created the bubble, and large scale wealth transfer from low end of the market to the high end. Don't get me wrong, some lose their shirts on the high end, but overall, this sort of 'managed credit crisis' acts as an overall wealth pump from the low end to high end of the market, not due to conscious planning of the crisis on the part of the financiers, but as a macro effect of micro-rules based on outwitting regulators to maximize short range profits. Problem is, though, so many other networks are nested and intertwined here, I mean, how do you take into account shifts in the fitness environment leading to the evolution of new financial technologies, all of which caused the setup for the model in the first place? This problem REALLY interests me, just not sure how to do it in a way that doesn't ignore these complexities. Ideas? [[Christopher Vitale|Chris]]

'''Notes from the margin (6/8/08 - John)'''

We need to keep this fairly simple. We're not trying to model the US economy. Let's stay focused on what questions we're trying to answer.

Two types of agents: borrowers and lenders.

''Borrower''

A borrower agent is described by its credit score. A credit score is an weighted aggregate of the following four attributes of the borrower:

35% — punctuality of payment in the past (only includes payments later than 30 days past due)
30% — the amount of debt, expressed as the ratio of current revolving debt (credit card balances, etc.) to total available revolving credit (credit limits)
15% — length of credit history
10% — types of credit used (installment, revolving, consumer finance)
10% — recent search for credit and/or amount of credit obtained recently

Credit score distribution in the US is:

[[Image: scorerangepercentage.png]]

As a first-order approximation, this can give us the distribution of “risk” profile among borrower agents. Additionally, depending on income (and perhaps credit score itself), value of the property being considered is probably a variable – that is, amount of the loan (certainly, the maximum one can borrow is related to one’s credit score). For the purpose of our model, we should just assume adequate supply of homes fitting the borrower agent’s borrowing capacity. And given the interest rate (and for some people, monthly payment), the borrower agent will either go for the loan or not (and shop around).

We need to also determine an agent’s propensity to borrow – what motivates an agent to decide to purchase a home, and how do we model that?

''Lender''

When a lender agent receives an application for a mortgage, it will process the application according to some pre-specified underwriting rules.

Some good information on underwriting practices can be found at:

[http://en.wikipedia.org/wiki/Mortgage_underwriting_in_the_United_States Underwriting]

Information on subprime lending and subprime crisis can be found at:

[http://en.wikipedia.org/wiki/Subprime_lending Subprime]

We need to come up with a simple algorithm for the lender agent in the model, which will determine if the loan will be made, and if so, return principal amount of the loan and term structure of the loan (fixed or variable interest rate and length of loan – and if the rate is to vary, rules for that). What are the key variables we can tweak to either encourage or discourage non-prime lending?

''And after the loan, so what?''

Certain percent of the loans will default. How do we model this? For the first model, we can assume some percentage of default rate, given the borrower agent’s credit score (hopefully, this data is available). When do they default (first year? Second year?...)? Can we make some simplifying assumptions (e.g., if you don’t default during the first five years, you won’t default, or something like that) for the first model – we can refine the model after we get the first, simple model working.

''Future Refinements we can consider for the model''

Lender agent’s ability to continue lending should be dependent on previous periods default history (some can/should go bankrupt), which should be directly related to its profitability.

Borrower agents will shop around (quality index for lender agent, based on the quality of its portfolio, or perceived "easiness" of getting the loan).

===Dynamics systems applied in networks===
A year or so ago I discovered this researcher[http://www.anarg.jp/~leibnitz/research.php] who uses "Biologically-inspired attractor-selection" methods to route data through a network. It's been a while since I read it, but I believe the idea is to use systems of differential equations to solve networking problems such as finding robust, energy-efficient or shortest paths. I think it would be an interesting project to use both network and differential equations to derive some results, analytical, numerical and simulation. The network need not be a computer network.

Pessimistically, the approach might be just "bullsh*t and hype", but if so, we could analyse and suitably criticise it, and perhaps develop a better approach. Regardless, if anybody is interested, feel free to speak to me (my crap laptop broke recently so I won't be on the net as frequently as usual).

[[Holger Keeler|Paul]]

I think there are a few of us (notably Ruben and myself) that are interested broadly in bio-inspired network stuff (e.g., routing, virus spread, artificial immune systems, etc.) Perhaps we could try to consolidate our interests into a single project. Thoughts? - Justin

Perhaps work by Lidia Yamamoto would be of interest: http://cn.cs.unibas.ch/people/ly/ -- [[Laura_Feeney|Laura]]

I think Kenji Leibnitz' work in bio-routing is conceptually very intersesting, but not entirely convincing from a practical perspective. But I would be happy to meet with people to disucss and look for a project in in this area. [[Laura_Feeney|Laura]]

My computer works again, for the time being. I'm not too focus on biologically-inspired methods necessarily, though they are interesting. I thought this method would be interesting, but now I realise they're stochastic differential equations which don't lend themselves to analysis as easily, I believe. However, it may be possible to ignore the stochastic term. I will sleep on it. Paul

=== Evolving organizational flexibility in dynamic environments ===

Inspired by Josh's model of evolving organizational hierarchy on Thursday, over lunch a few of us discussed how this could be enhanced in several ways. I think that the 'business' in the model can be considered analogous to human societies which have used different organizational structures to cope with differing dynamic environments, and perhaps have corresponding weakness or strengths in said environments. Many geographers/archaeologists consider the level of organizational complexity and inter-linkedness a key part of understanding the resilience and flexibility of a given society.

Some of the ways in which the model may be enhanced are:

# Encode more sophisticated adaptive strategies
# Add a cost of changing institutional structure, perhaps some sort of sunk-cost effect?
# Add more realistic dynamic environments

It is clear from historic human/environment interactions that some societies found it very hard to adapt to changing environmental conditions, and one possible explanation of this is that changing the structure of a society is non-linear process with thresholds, and for vulnerable societies crossing this threshold level was enough to cause collapse.

We could use historic case studies of failure (Norse Greenland, Easter Island) and success (Norse Iceland, many of the other pacific Islands, Japan) and ask, given we know the dynamics of the environment (though palo-environmental reconstruction) if the structure of the society had an impact on the success (or failure, i.e. mal-adaption) of that particular example.

[http://www.santafe.edu/events/workshops/index.php/Richard_Streeter Richard]

I'm interested: [http://www.santafe.edu/events/workshops/index.php/Steve_Hall Steve]

Me too. I'd like to hear about the cases: [http://www.santafe.edu/events/workshops/index.php/Catherine_Spence Cathy]

I can see some parallels between this and the classic tracking problem in control theory. I'd be interested. [[Srideep_Musuvathy|srideep]]

Antony and I have discussed a related problem. There are some recent results in biology relating the fitness cost of developing a sensor system to the entropy of a randomly varying environment. The dynamic environment in Josh's model could be generalized to such an entropy-parameterized environment, and one might expect a transition to the hierarchical structure (which is, more or less, a sensory system) as the entropy varies. [[Jacob_Foster|Jacob]]

===(Bayesian?) learning rates in biological and social systems===
Inspired by David Krakauer's lecture showing that evolution can be seen as a form of Bayesian learning, a question that naturally arises is how to measure learning rates in natural and artificial systems. In economics, [http://en.wikipedia.org/wiki/Experience_curve_effects learning curves and experience curves] are well-documented, typically following a power law shape. Can we quantify '''progress''' in biological, technological, and cultural evolution/development using this framework? Can we use '''efficiency''' as a universal measure? Also: what is the connection with the MEST-compression idea (Matter, Energy, Space, Time) of futurist [http://en.wikipedia.org/wiki/John_Smart_(futurist) John Smart]? (For example, think of future atomic neural nets mentioned by Alfred Hübler as a more compressed form of future intelligence than present state-of-the-art computing machines or brains).
Let me know if you'd like to brainstorm some of these ideas. [[B%C3%A9la_Nagy|Béla]]

=== An agent-based simulation of a pollination network===
Flowers need animals to visit them for reproduction, while these animals visit the flowers for food resources such as nectar. The pattern of interactions between flowers and insects can be thought of as a network of interactions. Different questions emerge in such network:

. What strategies flowers use in order to attract insects? What strategies insects use in order to visit the different flowers?

. What is the explanation for the specialization or the generalization of flowers and insects? why some flowers try to attrack a wide range of pollinators whereas other flowers specialize on a single species?

We would like to make an agent-based simulation based on an evolutionary game theory approach to try to find explanations for such questions and compare it with real data.

[[The pollination network wiki page]]

=== Structure Definitions===

At first sight, it seems obvious what a structure is. However, there are a
lot of different definitions of structure in use - in and between different
communities.

In the first meeting, I (Tanja) informed the others about my motivations for
looking at molecular structures based on RNA features: showing existing
definitions of RNA structure -- for example, minimum free energy, consensus
or abstract shapes, as well as discussing the importance of structure from a
phylogenetic viewpoint.

Moreover, we have had a short discussion about the ''Allegory of the Cave'' by Plato
and started discussing the following papers:

. Structure, Moshe Koppel, 1988

. Form and Content in Thinking Turing Machines, Oswald Wiener, 1988

Both in: The Universal Turing Machine / A Half Century Survey, edited R.
Herken, Springer-Verlag, New York.

We ended up with a lot of questions e.g. about TM, what is a sequence,
minimal descriptions, underlying structures, fundamental
structures, representatives, or the use of definitions in general - e.g
from a historical viewpoint, as well as to categorize them -- e.g. looking
at the purpose.

We already have different viewpoints in our group (e.g. architecture,
information theory, linguistics, logic, philosophy, computer science,
biology). At the last meeting, we decided to start a wiki page to play with
the different definitions between the fields and to prepare our next
meeting.

[[The structure definitions wiki page]]

We have already made an appointment for the second meeting:

9.00 on Wednesday, at Suite 3 (number 39 on the map), upper floor.

Somebody else, e.g from physics?

[[Tanja_Gesell|Tanja]]

I will bring what I can from physics.-- Craig

===Geometry of Fitness Landscapes===
As Dan mentioned today, the geometry of fitness landscapes is relatively unexplored terrain, with most of the underlying trait spaces being either simple (graph) or highly structured (Euclidean) . I've been interested in this topic for a while, so inspired by Dan's comment I thought I'd see if anyone else shared this interest. As a point of departure: there are some interesting articles in the Santa Fe volume on Evolutionary Dynamics, a paper by Stadler, Stadler, Wagner and Fontana (this latter regarding the underlying trait space), and some recent fancy work using computational algebraic geometry (which I don't understand entirely: http://www.biomedcentral.com/1471-2148/7/60/). As a related question, one might imagine exploring the "measurement theory" of fitness landscapes -- how do we reliably reconstruct the landscape geometry from finite measurements?

Anyone interested? (Sorry -- [[Jacob_Foster|Jacob]])

*I can't make out who posted this. I'd be willing to explore this a bit. I have some interested in algebraic topology, computational geometry stuff. However, it is not clear from the paper abstract what kind of 'computational algebraic geometry' they are talking about. [[Srideep_Musuvathy|srideep]]
*I might suggest looking at some of the work by Sergey Gavrilets as a stepping off point for some modern thought from biology on fitness landscapes. Poking around on the web to find a quick summary of some of his thoughts on Holey Adaptive landscapes I found this [http://www.cs.utk.edu/~langston/courses/cs594-fall2003/lecture27.html Lecture] he gave. It's long, but the end slides go into the meat and the begin provides a nice evolution of the ideas. [[Devin_Drown|Devin]]

On a related (but slightly less abstract) note, I am interested in modeling how interacting species co-construct their own and each other's fitness landscapes. I'm imagining an agent based model where each agent has "genes" which specify it's location in a fitness landscape, and also other genes which add some sort of random function to the landscape (as a very crude approximation, one could imagine using a mixture of Gaussians). As the species to evolve, you can watch how they move around in fitness space, and how they deform the landscape. This is an extremely rough idea, but I'd love to sit down and talk with some people about it. Maybe in a related discussion to one posted above.

Any takers? [[David_Foster|David]]

Something that came to my mind during the discussion of fitness landscapes was the idea of rate of adaptation to a dynamic fitness landscape. E.g. if the fitness landscape changes (e.g. climate) such that my current local maxima is now becoming a minima, how quickly must I explore the landscape to
esape extinction (dinosaurs seem to have failed this :-) Possibly interesting for both biological (antibiotic resistance, invasive species; climate change) and social systems (evolution of social systems in response to major technological change). Perhaps not enough data to do sensible work.

Any interest? [[Laura_Feeney | Laura]]

== Working Groups ==
=== Summary of Modeling Tools ===
A few of us were talking about how helpful it would be to have a summary of the common and useful modeling tools annotated with their inherent assumptions, best practices, pitfalls, etc. At the moment, we thought we would create a wiki page with this information. Please [[Characterization of Modeling Tools|stop by]] and comment on your favorite tool. In the future, we may bring all interested folks together to discuss and try to come to a consensus.

=== Evolutionary Game Theory ===
A few of us were thinking that there wouldn't be enough time to discuss enough topics in EGT in a [[CSSS_2008_Santa_Fe-Tutorials#A_Crash_Course_to_Classical_and_Evolutionary_Game_Theory|single tutorial]], so I decided to post an offer for a working group that could meet fairly regularly to read and discuss papers from the field, suggest new topics, and possible projects. So far we've thought about looking at evolutionary branching models (in, say, a colony of yeast that produces an enzyme that can be shared by all individuals of the colony) and extending them from one population to two.

Please let me know if you'd be interested in joining. Feel free to add your name and topics you'd like to discuss. 
—-[[User:Jreyes|Josh]]

 Update! This has been scheduled on Friday from 3 - 5, location TBD.

*I'm interested! Actually, I know nothing about the topic, but I think that it could help me in my research. There is an interesting article about segregation and game theory [[Media:Zhang2004.pdf|(Zhang2004)]]. Maybe this could serve as inspiration for a project. (Flavia)
*I'm interested too. [[Kathleen_Sprouffske|Kathleen]]

=== Viral Modelling ===
I (Jeremie) propose to set up a workshop on viral modelling (biomathematics, epidemiology, virus kinetics, evolution, networks...). The idea would be that anyone could prepare a short and general introduction to its research area.
Please let me know if you'd be interested in joining. Feel free to add your name and topics you'd like to discuss.

This sound like fun. All of the above are of interest to me. Alex

I'm interested - Paul

Great idea. I might have some info on computer network virus propagation that I could contribute. - Justin

Ok, I suggest meeting on thursday from 4.30. Let's say we could prepare a 15-20 min tutorial, just to see if we are on the "same page". How does it sound ?

Please put me on any lists for such meetings or tutorials. I am very interested! I have studied quasispecies theory some, but I have no hands-on research experience in any of this. [[Molly_Rorick|Molly]]

=== Social (and other?) Networks ===

There are a number of people who are doing work with or related to social netwworks. Is there interest in a social networks working group? Alternatively, in a more general working group on networks and network based methods (biological, social, etc)?

Show interest and maybe times for a meeting below:

[[User:Laura_Feeney|Laura]] -- I'm free this evening; maybe tomorrow evening before tutorial
[[User:Jeremie Guedj|Jeremie]] -- I'm interested also; free tomorrow evening !

I'd also be interested in this. Tomorrow evening sounds good. [[User: Mark_Rivera | Mark]]

Tentatively scheduled for 7pm -- [[Laura_Feeney|Laura]]

Can we move at 6? I would like to attend Béla's tutorial ... [[User:Giovanni|Giovanni]]

=== Theory Group ===
'''Update (6/08/08):''' Ok, here's the link for [[Theory Group Texts]] page. Post any texts and links you find here so we've got a central clearing house. Some possibilities mentioned were Bruno Latour, Indian philosophy and complexity, etc. Also, '''next meeting''', Tuesday, lunchtime, one of dining hall side tables. So far on agenda - trying to get some of the major terms from the Delanda (strata/network, double articulation, Bwo, agent/operator, intercalary agent, etc.) and discuss further implications of diagram/abstract machine and hierarchy/meshwork distinction.

The general will has spoken and set a rough agenda for our joint exploration of the weird intersections between continental philosophy, critical theory, and complexity. We'll start by reading selections from Manuel De Landa's A Thousand Years of Nonlinear History -- Introduction, Sandstone and Granite, Species and Ecosystems, Arguments and Operators, Conclusions and Speculations. There are several copies floating around (if you have one could you please post here and if you need one do the same). We'll meet Sunday afternoon, to avoid conflict with the hike on Saturday, specific time to be determined.

Update! First meeting 4:20 - 6:00 on Sunday, at the coffee shop/lounge area.

We've discussed several next steps, which I'll post after dinner :)
--[[Jacob_Foster|Hypothetical Hypochondriac]]

- Possible topics we threw around for further discussion - basic working intro to and/or discussion of any of the following thinkers that have been linked to complexity studies - Gilles Deleuze (rhizomatics, diagram/complex assemblages, virtual multiplicities, non-binary theories of language, desiring machines, nomadism vs. state structures, capitalism and desiring-production, major/minor sciences/social groups, networked models of mind, time and duration, intuition as method), Jacques Lacan (matheme-ization of the freudian unconscious, subject/language, master signifiers and social discourse production, ties to topology), Alain Badiou (ethics of the event, ties to cantorian set theory, mathematical ontology), Michel Foucault(decentered subject, disiplinary institutions, biopower, shifting epistemes), C.S. Pierce (process semiotics), Whitehead (process metaphysics), etc. Any ideas/suggestions? (Chris)

Spoken like a true volunteer, Chris! I would very much like an introduction to Deleuze. Peirce and Whitehead would also be fantastic. I would further propose that with many of these thinkers (Deleuze, Lacan, Badiou) we can have some very interesting discussions of the use, misuse, and abuse of technical/mathematical/complexity metaphors outside of the home field (or -- is there even such a thing as abusing a metaphor?) . How can such translation best be achieved? Lacanian mathematics would be an especially interesting angle in my opinion.

Another possibility: Leibniz and the "pre-history" of complexity science! Maybe reading the Monadology, etc.

I believe Tanja will post a link to Krakauer's Metahistory article, to support a broad conversation about History, laws of History, the dangers of such laws, etc.

--[[Jacob_Foster|Hypothetical Hypochondriac]]

Hey All- Ok, found some public domain texts, will keep posting them to my profile page, so far including some Deleuze, Badiou, etc. Chris

Thanks, Chris!
I am looking forward for our discussions about Deleuze and De Landa and
I would very much like an introduction to Lacanian mathematics. Futhermore, I would
also be interested in discussing the Monadology of Leibniz.
As mentioned in the last meeting, it would be nice to take a look at the following paper: The Quest for Patterns in Metahistory, by [http://www.santafe.edu/~krakauer/Site/Reviews_%26_Articles.html. David Krakauer], SFI Bulletin. (2007). In addition, a link to the frescoes in the
[http://www.giottoagliscrovegni.it/eng/home.html Cappella Scrovegni] by Giotto, which I mentioned in the previous meeting.

--[[Tanja_Gesell|Tanja]]

One more link: http://www.netbase.org/delanda/meshwork.htm
MESHWORKS, HIERARCHIES AND INTERFACES

Craig

=== Non-equilibrium thermodynamics and the production of entropy ===
I brought with me the textbook [http://books.google.com/books?id=YRjfuEP_QycC&printsec=frontcover&dq=non-equilibrium+thermodynamics+and+the+production+of+entropy&ei=N19HSP-KCoHIigHFiczqBA&client=firefox-a&sig=sXSiqzPEHeNMOjPuyf986eR6Ljc "Non-equilibrium thermodynamics and the production of entropy" by Kleidon and Lorenz] and I have been trying to understand over the last 6 months what it is all about. The claim is that Nature, whatever in turbulence, life or either markets, tries to maximize the entropy *production*. As Stephen Guerin mentioned earlier this week in one of his lecture, entropy increases but when the system is sufficiently nonlinear, the entropy increases the most rapidly possible. Such overall principle enables to predict the evolution of the system. The book has several chapters showing where his principle could be used: turbulence, mean state of the atmosphere of Earth as well as other planets, the shaping of landscape by water, the coupled evolution of the biosphere and atmosphere, Gaia, economic processes, etc. As long as I do not understand where that principle comes from, I will stay skeptical of those claims. Still, if they are right, this can have important consequences in many fields. Go take a look at the book and if you are interested or if you know something about it, drop me a word. Chuss

[[Francois_Ascani|Francois]]

=== "Speculative" Neuroscience ===
Meet to discuss neuroscience problems and, ideally, cutting edge research. I have Kandel's reference text and Arbib's Handbook with me, and will bring them along for the ride and for background. Would also like to speculate on what's going on in your brain and mind :) Maybe we can meet this weekend sometime, or tonight (5/6) at SFI?

[[Nish_Aravamudan|Nish]]

Hi Nish, I'm interested (see also my notes above). I could meet early this evening, but otherwise I'll be away for the weekend. Please let me know a time for the evening. Otherwise, I'll set up a tutorial (aiming for a Wednesday AM time next week -- that work for you?) and see if there's interest among other folks. Cheers, [[User:Sayres|Sayres]] 14:41, 6 June 2008 (MDT)

I'd be interested in throwing my thoughts around. I am not sure if you are going to discuss ideas at a neuronal modeling and analysis level or the behaviour and organization of a network of neurons. [[Srideep_Musuvathy|srideep]]

I already went through most of the Kandell textbook during a reading group last year and I would like to discuss more some new stuff like mirror neurons which in that textbook were not present, as well the biochemical aspects of the brain, which we ashamelessly skipped since most of the people in the group were AI folks! [[User:Giovanni|Giovanni]]

Count me in! [[Christopher Vitale|Chris]]

== BrainStorming Projects ==

=== Peter ===

Emergence of language in an agent-based model
*I am still interested(Petr).

=== Giovanni ===

"Evolving" interactions in M.A.S. (See above my project ideas) [[User:Giovanni|Giovanni]]

=== Riley ===

Prediction in cultural markets

=== Abby ===

Misinformation

=== Antony ===

Time-horizon of political institutions for managing global environmental goods

=== Mark ===

Social network data/evolution of networks

=== Skyler ===

Networks plus application of biological methods

=== Qiqi ===

Public goods gam, group cooperation, social network

...> group behaviour of CSSS 2008 
gathering data from all of us, including game theory and perhaps agent based modeling 

=== Tanja ===

Structure definitions

=== Jon ===

- Epidemic models of depression/anxiety
- Inference of stochastic models

=== Rio ===

Social-ecological system -> Resilience institutions

=== Flávia ===

Emergence of segregation from a game theory perspective.

=== Francois ===

1) I have a time series of Chlorophyll a taken over 20 years. A Nature paper has claimed that a chaotic model reproduce the observed time series. Simple question: is there any evidence that the observed time series itself be chaotic? That would be a simple application of the Nonlinear Time Series Analysis introduced by Liz. May just be a nice exercise to do, not necessarily a final project. let me know if interesting in helping me.

2) Lattice-Botlzmann models are quite like the Agent-Based models but they seem better adapted to reproduce fluids in motion: the code is short and I have a couple of them that I got from open sources. I never used them but if anybody is interested to play with it, let me know. we could use the sand table that Redfish has and maybe reproduce some cool stuff such as the flooding of a valley, the breaking of a dam, or something like that!

3) what about the climate? nobody interested? this is one of the most *complex* system. we could try our hands on simple conceptual model of the climate?

[[Francois_Ascani|Francois]]

Hi, Francois. I'd be interested in helping with (1). Would love to speculate about (3), though I don't have much background. -[[Sarah_Cobey|Sarah]]

(1) Sounds interesting - The unAustralian Paul

I've had some experience in dealing with problems similar to (1). (3) is an interesting problem - we could play around with the lorenz equation or look at temperature data. I might be interested in in exploring the question as to whether 'global warming' can be reduced or if we were to try and reduce it, can we be certain that we do not over react! This is an interesting problem and I would like to get my feet wet in this sea of ideas. [[Srideep_Musuvathy|srideep]]

CSSS 2008 Santa Fe-Tutorials

2008-06-09T04:21:31Z

Drown: /* Economics & Finance 101 */

{{CSSS 2008 Santa Fe}}



== The big opensource tutorial ==

=== Open Source research software ===

Update! [[Opensource software tutorial|Tutorial]] scheduled on Monday 9 from 7:00p

Open (no pun intended...) your eyes to the wonderful world of FOSS -- Free and Open Source Software. While the distinction between Free and Open Source is a very interesting one (and highly contentious in the right crowds), for research purposes, we want to use the best tools for the job but some of us suffer from limited income, so I would like to talk about both. At the same time, FOSS is great to use for a non-economic reason: if you find bugs, or design extensions, you can fix them yourself (in OSS, at least) or at least report the problem back to a typically active community. Some potential tools to discuss/explore: R, Octave, Scilab, Gnuplot, perhaps some of the more useful languages in the field like Python and perhaps others I don't know as much about (a quick `apt-cache` on my Ubuntu Hardy install shows RasMol, ClustalW, SeaView, Achilles, complearn, EMBOSS, GENESIS, etc...)

- I would like to give a "Brazilian" contribution. Those who are interested in GIS&Cia could have a look at [http://www.dpi.inpe.br/gilberto/software.html Free and Open Source GIS Source].
[[Flavia_Feitosa|Flavia]]

I would be happy to contribute a little bit about freely available simulation environments like ns-2 (computer networks) and omnet++ (a generic DES) -- Laura

- For Python I can offer a tutorial (see below). Nish, do you have any experience with [http://www.sagemath.org/ Sage]? [[User:Giovanni|Giovanni]]

All great ideas and I would love to have more of a "You know how to use this tool or you know of this tool, you talk about it" style of tutorial :)
Maybe we can do a general OSS tutorial/discussion and then transition to specific sub-topics in separate tutorials (Python, GIS, networks, etc)?
I've not used Sage, before, but I'm happy to take a look before the tutorial. Thanks for the info, Giovanni!

 
I'd like to learn more about open software. [[Holger_Keeler| Paul]]

Some subtopics that we'll cover:

==== R tutorial ====

I (''[[Ruben_Kubiak|Ruben]]'') know a little bit about R (basic stuff such as common plots and regression analysis) but would like to enhance my R skills. Does anybody have an interest in a R tutorial, too? Please edit this if there is more interest.

I am fairly familiar with R and could probably run a tutorial... what are you all interested in
learning? - Skyler
*I'd just like to get an understanding of some of it's practical uses. -Devin
*Do you familiar with running social network analysis package in R? I want to learn more about it. [[Jiang_Wu| Jiang]]

Interested folks
#[[Devin_Drown|Devin]]
#[[Mark_Rivera | Mark]]
#[[Jiang_Wu| Jiang]]
#[[Molly_Rorick|Molly]]
#(Soumya)
#[[Riley_Crane]]
#[[Jeremie]]
#[[Tanja_Gesell|Tanja]]

==== Python tutorial ====

I've (''also [[Ruben_Kubiak|Ruben]]'') interest in a Python tutorial. Please edit this if there is more interest.

I can give a tutorial on python and on scipy/numpy. I can also talk about coding in general, as python is both a languange which is object oriented, imperative and functional (somehow). We can use the [http://docs.python.org/tut/tut.html python tutorial] itself as a reference for the part about the language, and then move to the basic concepts of the duo [http://numpy.org numpy] / [http://scipy.org scipy], which form a powerful tool to manipulate n-dimensional arrays of numbers and also talk about [http://ipython.scipy.org/moin/ ipython] (the enhanced interactive shell) and the [http://matplotlib.sourceforge.net/ pylab] interface, which gives a very nice environment for interactive programming and data analysis. Since pylab has been designed to mimic MATLAB's interface (the major plotting/statistical functions work as expected in both enviroments, which saves you a lot of time if you're used to MATLAB), I can also talk a bit about MATLAB, but being not a big fan of it, it would be better if somebody else stepped in to another tutorial on that.

Leave a mark if interested! [[User:Giovanni|Giovanni]]

I'd be interested in this as well [[User: Mark | Mark]] 

I'm in. —[[User:Jreyes|Josh]]

I'm in. [[Nish_Aravamudan|Nish]]

Yes please. [[Molly_Rorick|Molly]]

Me too. [[Rory_Sayres]] [[User:Sayres|Sayres]] 23:55, 4 June 2008 (MDT)

I'd be interested in this as well [[Tanja_Gesell|Tanja]]

I'm in [[Riley_Crane]]

Another one. [[Petr Svarc|Petr]]

== Neutral models in biology ==

Already met. Big thanks to Molly!

There is an interesting [http://arxiv.org/abs/0710.4911 paper] by Cosma Shalizi of SFI about methodological problems in social sciences research in which he talks about the concept of neutral models in evolution models. I was wondering if any of the bio-people can give a tutorial on this topic as I am pretty interested in understanding the concept. [[User:Giovanni|Giovanni]]

I would be very interested in learning about neutral networks too! - Skyler

== GIS / Spatial Analysis ==

Space Matters!! Geographical information system (GIS) is a computational system (hardware + database engine) that is designed to assemble, store, update, analyze, manipulate, and display geographically referenced information (data identified by their locations).

I'm thinking about introducing some basic GIS concepts and a free GIS software known as [http://www.dpi.inpe.br/~flavia/GIS/ Terraview]. We could also explore some spatial analysis techniques (this is the best part!) using Terraview and [http://www.geoda.uiuc.edu/downloadin.php GeoDa] (also free!).

Please edit here if you are interested or send me an email. [mailto:flafeitosa@gmail.com Flávia]

Update! It has been scheduled on Friday, June 13 from 1:30 p.m. - 2:45 p.m.

I'm in [[Walter_Zesk|Walt]] 
I'd do this. —[[User:Jreyes|Josh]] 
let me know, I'm in, Sonja 
Me too. —[[User:Lfriedl|Lisa]] 
Can not wait for this! Rio 
Me too. [[Kathleen_Sprouffske|Kathleen]] 
Sounds like fun. If people are interested, I can bring some data sets to play around with. Alex

== Statistical Physics for Non-Physicists ==
Problem: Textbooks about this are written for physicists.
Solution: A Physicist (or mathematician) that would be so kind and spend few minutes (or maybe hours) to explain all that stuff to people like me(Petr):-)

[[Ruben_Kubiak|Ruben]]: Do you seek for a general introduction or something specific?

A crash course in Statistical Physics would be awesome. Let us know. — [[User:cyepez|Carlos]]

I am interested too. (Soumya)

Me too. (Jean)

Interested! [[User:Meritxell|Meritxell]]

Interested! [[User:Giovanni|Giovanni]]

Ditto - Skyler

Me too. —[[User:Lfriedl|Lisa]] 

Me three. [[User:RobMills|RobMills]]

I'd be willing to run such a tutorial. However, I would have to consult with some/all of the interested parties to find out what kind of statphys you want to learn about. There are a huge number of possible topics, one could start with basics like ensembles, or perhaps people are interested in master equation and other non-equilibrium techniques, or maybe critical phenomena is what people are interested in. I really do not know. (Orion)

Can you give us who are not physicists an introduction about a kind of special questions that you will think it from the viewpoint of physicists? Like complex network, dynamic, also something else, what is the most important measurement and dynamic process you want to observe? -[[Jiang_Wu|Jiang]]

== Modern Logic and Reasoning ==
Like I mentioned in the 'ice-breaking', I could tell something about application of modern logic into human reasoning. It's a very board topic, and very new. Criticisms are welcome and needed. I would give some basic examples. On top of that, I would also say some development of logic, and how I found it useful in research, which might seem un-related to logic, esp. in social science. I am planning to give a 15 to 20 minutes presentation, UNLESS people want to hear more, in that case, please let me know.
QiQi

I'm interested! [[Kathleen_Sprouffske|Kathleen]] 
Me too! [[kolbjorn|Kolbjørn]] 
Sign me up. — [[User:Jreyes|Josh]] 
I'm interested too! (Flavia) 
I'm in! [[Srideep_Musuvathy|srideep]] 
I'm in too [[User:Giovanni|Giovanni]] 
Count me in - Skyler 
I'd be interested in this as well. [[Tanja_Gesell|Tanja]]
 Sounds great - i'll be there. [[User:RobMills|RobMills]]

Please remind by email or somhow.. and sign me up! [[User:sonotto|Sonja]]

I am in Qi, But where? Rio

Update! Time at June 10th, 03.15 p.m. - 03.35 p.m.
[[CSSS 2008 Santa Fe-Schedule]]

== Introduction to the Design and Analysis of Computer Experiments ==
How do you find "interesting" behavior when your computer model is too slow or the inputs are too many to try every possible combination? Using an Arctic sea ice simulator example, I will show you how modern statistical methods can help you explore your virtual world more efficiently. Check out this brief
[http://www.stat.sfu.ca/~dbingham/NICDS_CompExpt/research.html overview] or a more technical paper about
[http://www.schonlau.net/publication/jogo98.pdf global optimization]. Also see [http://www.gaussianprocess.org/ Gaussian Processes for Machine Learning] for a list of available resources. [[B%C3%A9la_Nagy|Béla]]

== Genomics / Central dogma overview ==
It seems like some of you might be interested in an overview of the central dogma of molecular biology to non-biologists. This could be an 1h tutorial on the major actors of gene expression: nucleus, chromosomes, chromatine, DNA, RNA (tRNA, mRNA), proteins, polymerases, ribosomes, transcription factors, and eventually a quick intro to small, non-coding RNAs as a bonus. Although being a bioinformatician by training, I'm happy to leave the way if a "hard core" biologist wants to do this tutorial (Molly ?). Edit if interested! Jean

I'd be happy to attend a tutorial in 'genomics for idiots' -- Laura

Me too. I am also interested in metagenomics if this is not too much of course. -- Francois

I'd like to go to a 'genomics for idiots' tutorial as well. -- [[Srideep_Musuavthy|srideep]]

Ok, so I'll prepare some slides. How about Monday 9th, 5p - 6p (location TBA) ? -- Jean

== Artificial Intelligence/Machine Learning ==
I (Nish) could introduce some of the basic methods in AI/ML. If there is significant interest in the two fields separately, I could do two tutorials. Would probably focus on the higher level, rather than the nitty-gritty details, as well as applications of the methods to real problems. I'm not necessarily an expert, although have a fair amount of experience in the area, so I would prefer a more interactive session, where questions can be answered by everyone.

Sign me up. — [[User:cyepez|Carlos]] 
I'm also interested. -[[Sarah_Cobey|Sarah]] 
Me too! [[Flavia_Feitosa|Flávia]]

How about "AI/MI for dummies", Nish? I've been wondering about it.... Rio

sounds good [[Riley_Crane]]

== A Crash Course to Classical and Evolutionary Game Theory ==
Game theory is the study of interactive decision making. Classical game theory aims to develop a general theory to describe how rational agents interact strategically. In many cases humans lack the kind of infinite computational power and time assumed by classical game theory. In the early 1970s the biologist John Maynard Smith introduced evolutionary methods to the field, dispensing with the assumption of hyper-rationality while changing many of the concepts central to the field along the way. The result was evolutionary game theory. This new framework has been used to model the behavior of fundamentally non-rational players (such as viruses) as well as humans.

In this tutorial, I'd try to introduce the basic concepts in both of these fields, namely, the definition of a game, payoffs, the Nash equilibirum and evolutionarily stable strategies, the replicator dynamics. I'll briefly mention the three basic classes of two-strategy games represented by the Prisoner's Dilemma, the Snowdrift Game (sometimes called the Hawk-Dove game or Chicken), and the Stag Hunt Game. Depending on particular interests of the group, we could prove the Bishop-Cannings theorem and give a classification of all symmetric two-strategy games; or look at updating methods and spatial chaos; reputation and image scoring; rock-paper-scissors in biological systems; or evolutionary branching and specialization.

If there's something else you'd like to know about EGT, shoot me ([mailto:joshua.reyes@removeme.gmail.com Josh]) an email, and I'll see if I can dig up something I know on your topic. I'm not going to require any fancy mathematical background. If you've seen a 2×2 matrix before, great. Otherwise, it's not a big deal. We won't multiply them or calculate their eigenvalues. They'll just serve as a means for bookkeeping.

Note: Some of us are also thinking about setting up a [[CSSS_2008_Santa_Fe-Projects_%26_Working_Groups#Evolutionary_Game_Theory|working group]] as well. 
Update: The next meeting has been scheduled for Tuesday, June 10 from 7–8pm in a location TBD.

=== Lecture Notes ===
Lecture 1. [[Media:EGT-01.pdf|Classical Game Theory]]

Please let me know about any typos, errors, or flat-out lies. Suggestions are good, too. Thanks.

*I'll sign up for this. Kolbjørn
*I'm interested too! (Flavia)
*I'll be there too. Kathleen
*I'm in. Jean
*I'm interested as well. Steve
*will be there at 3 [[Walter_Zesk|Walt]]
*I'll be there, Petr
*Good stuff. I could also say a few things about [http://www.iiasa.ac.at/Research/EEP/AdaptiveDynamics.html adaptive dynamics], if there's interest. [[Sarah_Cobey|Sarah]]
*I'll be there. [[Jiang_Wu|Jiang]]
*Count me in (Chris)
*I'm in. Tanja

== Resilience of social-ecological systems ==
The resilience perspective is increasingly used as an approach for understanding the dynamics of social–ecological systems. Essential for the resilience perspective is the recognition that living systems are not in equilibrium but rather in a domain of attraction.
Many dynamic systems, however, have multiple domains of attraction. Moreover, self-organizing processes can create or change the shape and depth of this domain of attraction. Within the resilience perspective, new pathways of sustainable development can be represented by crossing a threshold from a domain of attraction and/or by creating new domains. Resilience is a measure of how much change or disruption is required to transform a system from being maintained by one set of mutually reinforcing processes and structures to a different set of processes and structures.
If you are interested we (Mike and Dirk) can introduce you to some of the insights developed by the [http://www.resalliance.org/1.php resiliance alliance] and the challenges we face in understanding these kind of systems.

I am interested in this too. Richard

Very interested, any idea of when you will do it? [[Walter_Zesk|Walt]]

I'm interested as well. Steve

I'm interested too. - Skyler

I think to contribute from my previous work on SES. Rio

== Introduction to classical control theory ==
I (Srideep) can offer a 'quick' tutorial on control theory/control systems. This is will be a simple introduction to the motivation, basic ideas, issues and jargon in the field. If you are interested, please let me know about your background in linear algebra, complex analysis and calculus. Depending on the background, I might spend more or less time introducing the field.

Ideally, if you know what eigenvalues and eigenvectors of a matrix are, what a pole of a complex function is and how the solution of a linear differential equation looks like, you are ready to jump right into controls. If the words above don't mean much at all, then we can run a quick 'review' of what they mean intuitively.
you can sign up here or send me an email [mailto:srideep.musuvathy@gmail.com srideep]

Update! Lets plan on discussing this early next week. Will fix up a time by the end of this week. Liz bradley will be done with her introduction to dynamics and the eigenvalue, eigenvector tutorial will be done this friday. This will make my life easier! :-)

I'd be very interested in this tutorial. I think I'm basically OK on the prerequisites,
but I wouldn't be annoyed by a review. Perhaps Monday? -- Laura

I'm in too. I guess I should be ok on linear algebra, calculus and linear ODEs, but I don't know what the pole of a complex function is. Jean

I'm in. If we can start with 'pole' thing, that would be wonderful. - Masayoshi

Hi Srideep, please put me in this group. About my background on the subjects you asked; zero!!! Sorry. Rio

Definitely interested in this. - Jacob

I'm in. Paul

Looks cool. -[[Sarah_Cobey|Sarah]]

Me too! [[Rory_Sayres|Rory]]

== Topology/algebra ==
I (Srideep) will also be happy to talk about topology, introducing the concepts of point-set topology. The language of modern mathematics is enshrined in the concepts of point-set topology. I can also talk about group theory and introduce abstract algebra to those interested. In my opinion, it is the most powerful gateway into abstract thinking. sign here or email me [mailto:srideep.musuvathy@gmail.com srideep]

I'd be very interested in that. Jean

I'd be interested to see what you cover in the topology section. Algebra, however, is for the birds :) Paul

Srideep, can you do an introduction to category theory? Or would you be interested in co-organizing a tutorial with me? - Jacob

I'm very interested. Abby

Sounds like fun (Chris)

== Eigenvalues - what are they and how to find them? ==
I (Kolbjørn) can put together a brief and elementary introduction to eigenvalues and eigenvectors if anyone have an urge for this. Sign up or e-mail and we'll schedule something. [mailto:kolbjorn@chalmers.se Kolbjørn]

UPDATE 06062008: SLIDES

[http://www.santafe.edu/events/workshops/images/e/e7/Linear_algebra_tutorial.pdf Tutorial slides]

UPDATE! Time: Friday June 6th, 01.00 p.m. - 03.00 p.m. If this collides with other stuff, please yell out! [[CSSS 2008 Santa Fe-Schedule]]

Yes please. [[Kathleen_Sprouffske|Kathleen]]

I am also very interested [[Walter_Zesk|Walt]]

I'm in as well [[ Mark_Rivera|Mark]]

Please - have always been kind of confusing to me. [[Jonathan_Zelner|Jon]]

Let me in - Masayoshi

I'm also interested! [[ Flavia_Feitosa|Flavia]]

I'll be there. -[[Molly_Rorick|Molly]]

I'm in as well. -[[Tanja_Gesell|Tanja]]

Me too! '''Just to remind'''; I think Classical and Evolutionary Game Theory (Josh)will be started at 3 PM. Rio

== How your computer works ==

Nish and Laura can give a joint tutorial on 'how your computer works'. What happens when I type 'www.santafe.edu' in my browser? How does a web server at santafe.edu handle all those incoming requests? What happens when I use a WiFi access point? Basically, we'd be happy to take your questions about how your computer works and do our best to answer them - we're also happy to have other co-tutors.

Let us know if there's interest [mailto:lmfeeney@sics.se Laura], we'd probably schedule later next week, to not conflict with tutorials that focus on maths and other project prerequisites.

I would love this. -[[Sarah_Cobey|Sarah]]

== How your hardware works ==
Along the same lines as the computer tutorial, I've found myself discussing hardware with a number of folks. And why hardware matters from a massive parallelism perspective (which is quite common in the complex research areas I've encountered). If folks are interested, I can give a rough overview of the way hardware works in different types of computers and supercomputers (as much as I understand of it) as well as how to best leverage that knowledge.

Not sure how this differs from the the one above it, but def. interested (Chris)

== Computational Physics for Non-physicists or A small introduction into Applied Physics ==

I've seen that many people are interested in physics. I could give an introduction to "computational" physics - this means physics with a PC. Actually, it is very broad and gives some basics for simulations (interesting for all simulation-folks):

- What is a 'random number generator' and why should I know something about it?

- What are Master-equations?

- The Ising-model / Voter-model

- The Central Limit Theorem or why does it make sense to average over multiple runs of a simulation?

- ...

[[Ruben Kubiak|Ruben]]

I'm very interested [[Nish_Aravamudan|Nish]]

I'm in too. [[Jiang_Wu|Jiang]]

[[Srideep_Musuvathy|srideep]] is in.
Sounds great. [[Molly_Rorick|Molly]]

Looking forward to it. [[Petr Svarc|Petr]]

==Information Theory==
An open discussion of Shannon information theory (would like some help in presenting this part clearly) and then some newer results from its application to cellular automata (and potentially other complex systems).

Interesting. I remember something from the master course I took. [[User:Giovanni|Giovanni]] 
I'd love to participate. -[[Sarah_Cobey|Sarah]] 
I'm interested.[[Holger_Keeler|Paul]] 
I'm in. --[[User:Lfriedl|Lisa]]

I'm in. --[[User:meritxell|Meritxell]]

FYI: Tom Carter is going to be talking about Information Theory a bit tomorrow from 2-3pm, not sure of a location yet, but its on the schedule.

==Cellular Automata==
CAs (particularly ECAs) are a very interested model of computation. How do 8 rules (ECA 110, e.g.) emulate a Turing Machine? Why is that interesting? What can we learn about what defines computation given CAs? Maybe we can also discuss some simple computational (Turing) theory.

I'd go to that twice. —[[User:Jreyes|Josh]]

Sounds like fun. [[Christopher Vitale|Chris]]

==A little analytical tool-box: Non-linear dynamics, ODEs, PDEs...==
The [[David_Foster|Brothers]] [[Jacob_Foster|Foster]] would be happy to offer some tutorials on analytical methods. Depending on what Alfred Hubler covers, we can do some fraction of Strogatz (flows on the line & circle, bifurcations, maybe linear systems, index theorem, etc.), as well as offering a basic introduction to solving linear ODEs (no theorems, just techniques) and simple PDEs like the heat equation, with boundary conditions. Ideally this would come after Kolbjørn's eigen-stuff course, so we can just assume familiarity with that.

We've put a tentative time for our tutorial on the schedule: [[CSSS_2008_Santa_Fe-Schedule#Week_Three_-_FINANCE/ECONOMY|June 16 at 3:15pm]]. Let us know if this doesn't work out for some reason and we can try to change it.

These are fun topics! I never get enough of them! -- [[Srideep_Musuvathy|srideep]] 
Sounds great. [[Molly_Rorick|Molly]] 
Interesting -- sure. [[User:Lfriedl|Lisa]] 
Very useful! [[Kathleen_Sprouffske|Kathleen]] 
Need this.... Rio 
I'm in! [[Flavia_Feitosa|Flávia]]
great! [[Riley_Crane]]

Brothers Foster rulez! I'll be there. [[Petr Svarc|Petr]]

==Linguistics==
Can someone (I don't know [[Peter_Graff|who]]) perhaps offer a tutorial on basic linguistics stuff? I am particularly interested in generative grammar and coverage of the Chomsky "Three Models" paper, but maybe there are more interesting topics to be discussed these days... -Jacob

I could easily do a Saussure/Pierce tutorial, along with how this has been applied from everything to kinship structure to film theory to table manners, but this is continental structural linguistics, very diff from the chomsky stuff. I think Peter Graff can do the chomsky stuff, though, perhaps we could work on this together (Chris)

Would love both tutorials. Esp. the kinship structure stuff (is this Andre Weil's algebra chapter on kinship, from Levi-Strauss I think?) -Jacob

I'd love to participate. -Tanja

==Fitting models to data==
A few people have asked me for a brief review of fitting models to data, but I'd like to know what methods interest you. I could start with least squares and progress to Bayesian approaches, maximum likelihood, and some more recent developments in methods for exploring space (GAs, particle filters, MCMC) with which I'm familiar. I'm by no means an expert in all these topics, so please add your name below if there's something you'd like to learn about (a particular method or method for a particular context) or teach. I feel like this tutorial would be most appropriate for the third or fourth week. -[[Sarah_Cobey|Sarah]]

I am really interested in this. (Soumya)

cool [[Riley_Crane]]

==Networks, Sign Systems, and the Mind==

So, as an outgrowth of the (continental) theory/philosophy working group, I've come up with two ideas for tutorial/discussion sessions on stuff people might be interested in, in which I'd likely throw some materials at the group, then see where discussion takes us. The first one would be on theories of language and the mind. Probably start off with the first real theory of language and the brain, Freud's topological theory, and then move to how this was absorbed into structuralist linguistics/semiotics in the 1950's (Saussure's theory of signifiers, Jakobsen on axes of discourse, paradigms/syntagms, metaphoric value transfer, and how this was applied to kinship structures, social institutions, etc.) From there we could look at how Jacques Lacan built upon this with his 'mathemic' algebraic notation for discourse analysis. We could then look at how networked theories of mind challenge both the Lacanian model and its American counterparts (Fodor's psychosemantics, for example), particularly in regard to connectionist architectures in artificial neural networks, and how this leads to more distributed notions of linguistic structure. These new paradigms can allow us to move beyond notions of discrete 'signs' existing somewhere in the brain to models based on research in microfeature maps, dynamic network synchronization, spreading activation, and feature vectores. When synthesized with Lacan's insights, and blended with some ideas from object-relations theory and by thinkers like Marvin Minsky and Gerald Edelman, its possible to come up with models that actually reflect the impact of complex systems theories. Likely wayy too much stuff to squeeze in, but certainly enough to get a conversation going, even if we don't get to half of it!

Anyone interested? (-Chris)

== Questions at the Intersection of Neuroscience and Complexity ==

Update! This tutorial is scheduled for 10:30 AM Wedenesday (June 11), in the small library on the upper floor of Petersen student center, just behind the main conference room.

Related to Chris' proposal above, but perhaps on the flip side, I'd be happy to give a tutorial / lead a discussion on issues where questions of complexity intersect with problems in neuroscience. I'll distinguish this topic from the idea above, in that I'll focus a bit more on bottom-up questions rather than purely theory-motivated questions. Neuroscience is a very large field, so I'll talk about some of the things I know, but encourage others to bring their own knowledge and curiosity.

I'll start with a short background on neuroanatomy of humans and other species. Then I'll do a survey of what's sometimes termed "systems neuroscience". This is the branch of neuroscience that asks about behavior roughly on the level of neural circuits -- but which often jumps up and down scales, and overlaps pretty significantly with ideas in "cognitive neuroscience" where the focus is on a lot of the interesting, higher-order behaviors unique to relatively few species. Then I'll go over a couple of papers which I think start on a road to using complex systems. Examples of what I might talk about would be:

* [http://www.ncbi.nlm.nih.gov/pubmed/17428910?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum Kiani et al J. Neurophys 2007] '''Does the visual system naturally group objects into heirarchical categories?''' These authors tried to apply some dimensionality reduction techniques to neural data from monkey inferotemporal cortex. The ideas from Dr. Newman's lectures may be very appropriate here.
* [http://www.ncbi.nlm.nih.gov/pubmed/17660812?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum Assisi et al. Nature Neuroscience 2007] '''Sparseness in representation of odors'''. The Laurent lab has been combining high-quality experimental methods in the insect olfactory system with computational models (including network models) to look at how the insect system (and more recently the mammalian system) represent odors. The system presents a very interesting contrast to the visual system, in terms of the sparseness of representations at the early levels. There's some elegant circuitry mapped out here. '''BONUS QUESTION!''' I remember one of the questions they investigated earlier was how locusts transition from 'happy grasshopper' mode to 'Biblical swarm' mode. This has something to do with olfaction. This population behavior is probably a very intersting bifurcation; we can dig into what this reflects.
* [http://www.ncbi.nlm.nih.gov/pubmed/18047414?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum Machens and Brody, Neural Computation 2008]. [[http://www.molbio.princeton.edu/index.php?option=content&task=view&id=335 Carlos Brody]] does a lot of work on how neural circuits dynamics can allow for short term memory behavior. This includes comparing a perceived sensation to something you experienced a few seconds or minutes ago, and constructing an internal sense of how time elapses. His group uses tools like attractor networks to model this behavior.
* '''Walter Freeman's work'''. Freeman studies the mammalian visual system, but also has a background in talking about how neural circuits encode meaning. This will be an opportunity for me to go back and find some interesting results to discuss. We may also highlight the questions of information theory and oscillatory behavior in neural circuits, which covers researchers like Pascal Fries, John Huguenard, and David McCormick. I'll update this part with a more specific paper when I find a good one.

'''Timing?''' Right now I'll focus on Wednesday morning, June 11. Please let me know below if you're interested. If it's a small group we can meet in the small library next to the main room; this might encourage discussion. And of course, let me know if there's something within this area in which you're more or less interested.

Cheers, [[Rory_Sayres | Rory]]

I'll be there Wednesday AM. Teach me, oh wise Neuroscientist! [[Nish_Aravamudan|Nish]]

Hellsyeah. [[Christopher Vitale|Chris]]

==Network Economics and Value Theory==

So, for the third week of CSSS, I'm thinking of maybe doing a session on 'Network Economics and Value Theory' for whoever's interested. Likely start off with Marx's three levels of value (use, exchange, surplus), move to his theories on production, formulas for capital, commodity fetishism, sticky points of his famous 'labor theory of value,' then on to his analysis of modes of production, and his thesis on the falling rate of profit that was supposed to bring down capitalism (but which obviously didn't). From there we could discuss critiques/updates of this theory via the growth of Keynesianism/Stalinism/Neoliberalism, in order to get to David Harvey's new work on how neoliberal economies largely avoid demand crises by engineering carefully managed accumulation crises whose effects can be easily passed off to poorer nations using multi-national postwar institutions like the IMF/WTO. This leads to examples of how networked models can help us understand today's economic crises (for example, how evolutionary search models can help us understand the ways in which 'overleveraging' economies via 'market derivatives' can help funnel capital to hedge funds in rich countries). From there we could look at critiques of economic theories of value, particularly Deleuze and Guattari's notion of 'desiring-production' as that which links production of commodities to the production of consumers by the social unit of production, namely, the family, and how even this model needs to be rethought in terms of shifts in mass media. Other topics could include theories of network political activism, namely those of Hardt and Negri (Empire/Multitude) and Ernesto Laclau on social dislocations and crisis management via counterhegemonic blocs.

Anyone interested in any of this stuff, lemme know! (-Chris)

== Topological and Symbolic Dynamical Systems ==

I would like to address the perceived interest among [[Jacob_Foster|few]] of us here in topics relating to the topological dynamics and symbolic dynamics. I can talk a bit about ideas relating to the topological properties of dynamical systems and systems with very little structure to them (i.e., systems whose state spaces are merely a hausdorff space and a dynamic shift which is a continuous function). The symbolic dynamics part will deal with spaces of sequences of symbols and the dynamics being a shift map. I would like to wrap things up with a powerful tool - topological conjugacy - which allows us to define an 'equivalence' between two dynamical systems, one of which might be easier to understand and analyze. Ideally, this discussion will come after my topology tutorial, but I'll spend a few minutes describing formally and intuitively, the terms I use. Alternatively, we can form small discussion groups and chat about this over a cup of tea. [[Srideep_Musuvathy|srideep]]

absolutely interested. [[Christopher Vitale|Chris]]

== Economics & Finance 101 ==
A 1 hour mini crash-course on the basic principles of Economics and Finance. The aim of this tutorial is -hopefully- to give a heads up for the upcoming Economics/Finance week for people who do not have a background in Economics.
I will introduce 3 simple models of microeconomics, macroeconomics and finance that can give an idea of what economists do. [[Carlos_Yepez|Carlos]]

'''Date and time:''' Friday June 13, 3:00-4:00pm.

'''Note:''' Reply to this page if you are interested in taking this tutorial.
*[[Devin_Drown|Devin]]

CSSS 2008 Santa Fe-Tutorials

2008-06-09T04:21:14Z

Drown: /* Economics & Finance 101 */

{{CSSS 2008 Santa Fe}}



== The big opensource tutorial ==

=== Open Source research software ===

Update! [[Opensource software tutorial|Tutorial]] scheduled on Monday 9 from 7:00p

Open (no pun intended...) your eyes to the wonderful world of FOSS -- Free and Open Source Software. While the distinction between Free and Open Source is a very interesting one (and highly contentious in the right crowds), for research purposes, we want to use the best tools for the job but some of us suffer from limited income, so I would like to talk about both. At the same time, FOSS is great to use for a non-economic reason: if you find bugs, or design extensions, you can fix them yourself (in OSS, at least) or at least report the problem back to a typically active community. Some potential tools to discuss/explore: R, Octave, Scilab, Gnuplot, perhaps some of the more useful languages in the field like Python and perhaps others I don't know as much about (a quick `apt-cache` on my Ubuntu Hardy install shows RasMol, ClustalW, SeaView, Achilles, complearn, EMBOSS, GENESIS, etc...)

- I would like to give a "Brazilian" contribution. Those who are interested in GIS&Cia could have a look at [http://www.dpi.inpe.br/gilberto/software.html Free and Open Source GIS Source].
[[Flavia_Feitosa|Flavia]]

I would be happy to contribute a little bit about freely available simulation environments like ns-2 (computer networks) and omnet++ (a generic DES) -- Laura

- For Python I can offer a tutorial (see below). Nish, do you have any experience with [http://www.sagemath.org/ Sage]? [[User:Giovanni|Giovanni]]

All great ideas and I would love to have more of a "You know how to use this tool or you know of this tool, you talk about it" style of tutorial :)
Maybe we can do a general OSS tutorial/discussion and then transition to specific sub-topics in separate tutorials (Python, GIS, networks, etc)?
I've not used Sage, before, but I'm happy to take a look before the tutorial. Thanks for the info, Giovanni!

 
I'd like to learn more about open software. [[Holger_Keeler| Paul]]

Some subtopics that we'll cover:

==== R tutorial ====

I (''[[Ruben_Kubiak|Ruben]]'') know a little bit about R (basic stuff such as common plots and regression analysis) but would like to enhance my R skills. Does anybody have an interest in a R tutorial, too? Please edit this if there is more interest.

I am fairly familiar with R and could probably run a tutorial... what are you all interested in
learning? - Skyler
*I'd just like to get an understanding of some of it's practical uses. -Devin
*Do you familiar with running social network analysis package in R? I want to learn more about it. [[Jiang_Wu| Jiang]]

Interested folks
#[[Devin_Drown|Devin]]
#[[Mark_Rivera | Mark]]
#[[Jiang_Wu| Jiang]]
#[[Molly_Rorick|Molly]]
#(Soumya)
#[[Riley_Crane]]
#[[Jeremie]]
#[[Tanja_Gesell|Tanja]]

==== Python tutorial ====

I've (''also [[Ruben_Kubiak|Ruben]]'') interest in a Python tutorial. Please edit this if there is more interest.

I can give a tutorial on python and on scipy/numpy. I can also talk about coding in general, as python is both a languange which is object oriented, imperative and functional (somehow). We can use the [http://docs.python.org/tut/tut.html python tutorial] itself as a reference for the part about the language, and then move to the basic concepts of the duo [http://numpy.org numpy] / [http://scipy.org scipy], which form a powerful tool to manipulate n-dimensional arrays of numbers and also talk about [http://ipython.scipy.org/moin/ ipython] (the enhanced interactive shell) and the [http://matplotlib.sourceforge.net/ pylab] interface, which gives a very nice environment for interactive programming and data analysis. Since pylab has been designed to mimic MATLAB's interface (the major plotting/statistical functions work as expected in both enviroments, which saves you a lot of time if you're used to MATLAB), I can also talk a bit about MATLAB, but being not a big fan of it, it would be better if somebody else stepped in to another tutorial on that.

Leave a mark if interested! [[User:Giovanni|Giovanni]]

I'd be interested in this as well [[User: Mark | Mark]] 

I'm in. —[[User:Jreyes|Josh]]

I'm in. [[Nish_Aravamudan|Nish]]

Yes please. [[Molly_Rorick|Molly]]

Me too. [[Rory_Sayres]] [[User:Sayres|Sayres]] 23:55, 4 June 2008 (MDT)

I'd be interested in this as well [[Tanja_Gesell|Tanja]]

I'm in [[Riley_Crane]]

Another one. [[Petr Svarc|Petr]]

== Neutral models in biology ==

Already met. Big thanks to Molly!

There is an interesting [http://arxiv.org/abs/0710.4911 paper] by Cosma Shalizi of SFI about methodological problems in social sciences research in which he talks about the concept of neutral models in evolution models. I was wondering if any of the bio-people can give a tutorial on this topic as I am pretty interested in understanding the concept. [[User:Giovanni|Giovanni]]

I would be very interested in learning about neutral networks too! - Skyler

== GIS / Spatial Analysis ==

Space Matters!! Geographical information system (GIS) is a computational system (hardware + database engine) that is designed to assemble, store, update, analyze, manipulate, and display geographically referenced information (data identified by their locations).

I'm thinking about introducing some basic GIS concepts and a free GIS software known as [http://www.dpi.inpe.br/~flavia/GIS/ Terraview]. We could also explore some spatial analysis techniques (this is the best part!) using Terraview and [http://www.geoda.uiuc.edu/downloadin.php GeoDa] (also free!).

Please edit here if you are interested or send me an email. [mailto:flafeitosa@gmail.com Flávia]

Update! It has been scheduled on Friday, June 13 from 1:30 p.m. - 2:45 p.m.

I'm in [[Walter_Zesk|Walt]] 
I'd do this. —[[User:Jreyes|Josh]] 
let me know, I'm in, Sonja 
Me too. —[[User:Lfriedl|Lisa]] 
Can not wait for this! Rio 
Me too. [[Kathleen_Sprouffske|Kathleen]] 
Sounds like fun. If people are interested, I can bring some data sets to play around with. Alex

== Statistical Physics for Non-Physicists ==
Problem: Textbooks about this are written for physicists.
Solution: A Physicist (or mathematician) that would be so kind and spend few minutes (or maybe hours) to explain all that stuff to people like me(Petr):-)

[[Ruben_Kubiak|Ruben]]: Do you seek for a general introduction or something specific?

A crash course in Statistical Physics would be awesome. Let us know. — [[User:cyepez|Carlos]]

I am interested too. (Soumya)

Me too. (Jean)

Interested! [[User:Meritxell|Meritxell]]

Interested! [[User:Giovanni|Giovanni]]

Ditto - Skyler

Me too. —[[User:Lfriedl|Lisa]] 

Me three. [[User:RobMills|RobMills]]

I'd be willing to run such a tutorial. However, I would have to consult with some/all of the interested parties to find out what kind of statphys you want to learn about. There are a huge number of possible topics, one could start with basics like ensembles, or perhaps people are interested in master equation and other non-equilibrium techniques, or maybe critical phenomena is what people are interested in. I really do not know. (Orion)

Can you give us who are not physicists an introduction about a kind of special questions that you will think it from the viewpoint of physicists? Like complex network, dynamic, also something else, what is the most important measurement and dynamic process you want to observe? -[[Jiang_Wu|Jiang]]

== Modern Logic and Reasoning ==
Like I mentioned in the 'ice-breaking', I could tell something about application of modern logic into human reasoning. It's a very board topic, and very new. Criticisms are welcome and needed. I would give some basic examples. On top of that, I would also say some development of logic, and how I found it useful in research, which might seem un-related to logic, esp. in social science. I am planning to give a 15 to 20 minutes presentation, UNLESS people want to hear more, in that case, please let me know.
QiQi

I'm interested! [[Kathleen_Sprouffske|Kathleen]] 
Me too! [[kolbjorn|Kolbjørn]] 
Sign me up. — [[User:Jreyes|Josh]] 
I'm interested too! (Flavia) 
I'm in! [[Srideep_Musuvathy|srideep]] 
I'm in too [[User:Giovanni|Giovanni]] 
Count me in - Skyler 
I'd be interested in this as well. [[Tanja_Gesell|Tanja]]
 Sounds great - i'll be there. [[User:RobMills|RobMills]]

Please remind by email or somhow.. and sign me up! [[User:sonotto|Sonja]]

I am in Qi, But where? Rio

Update! Time at June 10th, 03.15 p.m. - 03.35 p.m.
[[CSSS 2008 Santa Fe-Schedule]]

== Introduction to the Design and Analysis of Computer Experiments ==
How do you find "interesting" behavior when your computer model is too slow or the inputs are too many to try every possible combination? Using an Arctic sea ice simulator example, I will show you how modern statistical methods can help you explore your virtual world more efficiently. Check out this brief
[http://www.stat.sfu.ca/~dbingham/NICDS_CompExpt/research.html overview] or a more technical paper about
[http://www.schonlau.net/publication/jogo98.pdf global optimization]. Also see [http://www.gaussianprocess.org/ Gaussian Processes for Machine Learning] for a list of available resources. [[B%C3%A9la_Nagy|Béla]]

== Genomics / Central dogma overview ==
It seems like some of you might be interested in an overview of the central dogma of molecular biology to non-biologists. This could be an 1h tutorial on the major actors of gene expression: nucleus, chromosomes, chromatine, DNA, RNA (tRNA, mRNA), proteins, polymerases, ribosomes, transcription factors, and eventually a quick intro to small, non-coding RNAs as a bonus. Although being a bioinformatician by training, I'm happy to leave the way if a "hard core" biologist wants to do this tutorial (Molly ?). Edit if interested! Jean

I'd be happy to attend a tutorial in 'genomics for idiots' -- Laura

Me too. I am also interested in metagenomics if this is not too much of course. -- Francois

I'd like to go to a 'genomics for idiots' tutorial as well. -- [[Srideep_Musuavthy|srideep]]

Ok, so I'll prepare some slides. How about Monday 9th, 5p - 6p (location TBA) ? -- Jean

== Artificial Intelligence/Machine Learning ==
I (Nish) could introduce some of the basic methods in AI/ML. If there is significant interest in the two fields separately, I could do two tutorials. Would probably focus on the higher level, rather than the nitty-gritty details, as well as applications of the methods to real problems. I'm not necessarily an expert, although have a fair amount of experience in the area, so I would prefer a more interactive session, where questions can be answered by everyone.

Sign me up. — [[User:cyepez|Carlos]] 
I'm also interested. -[[Sarah_Cobey|Sarah]] 
Me too! [[Flavia_Feitosa|Flávia]]

How about "AI/MI for dummies", Nish? I've been wondering about it.... Rio

sounds good [[Riley_Crane]]

== A Crash Course to Classical and Evolutionary Game Theory ==
Game theory is the study of interactive decision making. Classical game theory aims to develop a general theory to describe how rational agents interact strategically. In many cases humans lack the kind of infinite computational power and time assumed by classical game theory. In the early 1970s the biologist John Maynard Smith introduced evolutionary methods to the field, dispensing with the assumption of hyper-rationality while changing many of the concepts central to the field along the way. The result was evolutionary game theory. This new framework has been used to model the behavior of fundamentally non-rational players (such as viruses) as well as humans.

In this tutorial, I'd try to introduce the basic concepts in both of these fields, namely, the definition of a game, payoffs, the Nash equilibirum and evolutionarily stable strategies, the replicator dynamics. I'll briefly mention the three basic classes of two-strategy games represented by the Prisoner's Dilemma, the Snowdrift Game (sometimes called the Hawk-Dove game or Chicken), and the Stag Hunt Game. Depending on particular interests of the group, we could prove the Bishop-Cannings theorem and give a classification of all symmetric two-strategy games; or look at updating methods and spatial chaos; reputation and image scoring; rock-paper-scissors in biological systems; or evolutionary branching and specialization.

If there's something else you'd like to know about EGT, shoot me ([mailto:joshua.reyes@removeme.gmail.com Josh]) an email, and I'll see if I can dig up something I know on your topic. I'm not going to require any fancy mathematical background. If you've seen a 2×2 matrix before, great. Otherwise, it's not a big deal. We won't multiply them or calculate their eigenvalues. They'll just serve as a means for bookkeeping.

Note: Some of us are also thinking about setting up a [[CSSS_2008_Santa_Fe-Projects_%26_Working_Groups#Evolutionary_Game_Theory|working group]] as well. 
Update: The next meeting has been scheduled for Tuesday, June 10 from 7–8pm in a location TBD.

=== Lecture Notes ===
Lecture 1. [[Media:EGT-01.pdf|Classical Game Theory]]

Please let me know about any typos, errors, or flat-out lies. Suggestions are good, too. Thanks.

*I'll sign up for this. Kolbjørn
*I'm interested too! (Flavia)
*I'll be there too. Kathleen
*I'm in. Jean
*I'm interested as well. Steve
*will be there at 3 [[Walter_Zesk|Walt]]
*I'll be there, Petr
*Good stuff. I could also say a few things about [http://www.iiasa.ac.at/Research/EEP/AdaptiveDynamics.html adaptive dynamics], if there's interest. [[Sarah_Cobey|Sarah]]
*I'll be there. [[Jiang_Wu|Jiang]]
*Count me in (Chris)
*I'm in. Tanja

== Resilience of social-ecological systems ==
The resilience perspective is increasingly used as an approach for understanding the dynamics of social–ecological systems. Essential for the resilience perspective is the recognition that living systems are not in equilibrium but rather in a domain of attraction.
Many dynamic systems, however, have multiple domains of attraction. Moreover, self-organizing processes can create or change the shape and depth of this domain of attraction. Within the resilience perspective, new pathways of sustainable development can be represented by crossing a threshold from a domain of attraction and/or by creating new domains. Resilience is a measure of how much change or disruption is required to transform a system from being maintained by one set of mutually reinforcing processes and structures to a different set of processes and structures.
If you are interested we (Mike and Dirk) can introduce you to some of the insights developed by the [http://www.resalliance.org/1.php resiliance alliance] and the challenges we face in understanding these kind of systems.

I am interested in this too. Richard

Very interested, any idea of when you will do it? [[Walter_Zesk|Walt]]

I'm interested as well. Steve

I'm interested too. - Skyler

I think to contribute from my previous work on SES. Rio

== Introduction to classical control theory ==
I (Srideep) can offer a 'quick' tutorial on control theory/control systems. This is will be a simple introduction to the motivation, basic ideas, issues and jargon in the field. If you are interested, please let me know about your background in linear algebra, complex analysis and calculus. Depending on the background, I might spend more or less time introducing the field.

Ideally, if you know what eigenvalues and eigenvectors of a matrix are, what a pole of a complex function is and how the solution of a linear differential equation looks like, you are ready to jump right into controls. If the words above don't mean much at all, then we can run a quick 'review' of what they mean intuitively.
you can sign up here or send me an email [mailto:srideep.musuvathy@gmail.com srideep]

Update! Lets plan on discussing this early next week. Will fix up a time by the end of this week. Liz bradley will be done with her introduction to dynamics and the eigenvalue, eigenvector tutorial will be done this friday. This will make my life easier! :-)

I'd be very interested in this tutorial. I think I'm basically OK on the prerequisites,
but I wouldn't be annoyed by a review. Perhaps Monday? -- Laura

I'm in too. I guess I should be ok on linear algebra, calculus and linear ODEs, but I don't know what the pole of a complex function is. Jean

I'm in. If we can start with 'pole' thing, that would be wonderful. - Masayoshi

Hi Srideep, please put me in this group. About my background on the subjects you asked; zero!!! Sorry. Rio

Definitely interested in this. - Jacob

I'm in. Paul

Looks cool. -[[Sarah_Cobey|Sarah]]

Me too! [[Rory_Sayres|Rory]]

== Topology/algebra ==
I (Srideep) will also be happy to talk about topology, introducing the concepts of point-set topology. The language of modern mathematics is enshrined in the concepts of point-set topology. I can also talk about group theory and introduce abstract algebra to those interested. In my opinion, it is the most powerful gateway into abstract thinking. sign here or email me [mailto:srideep.musuvathy@gmail.com srideep]

I'd be very interested in that. Jean

I'd be interested to see what you cover in the topology section. Algebra, however, is for the birds :) Paul

Srideep, can you do an introduction to category theory? Or would you be interested in co-organizing a tutorial with me? - Jacob

I'm very interested. Abby

Sounds like fun (Chris)

== Eigenvalues - what are they and how to find them? ==
I (Kolbjørn) can put together a brief and elementary introduction to eigenvalues and eigenvectors if anyone have an urge for this. Sign up or e-mail and we'll schedule something. [mailto:kolbjorn@chalmers.se Kolbjørn]

UPDATE 06062008: SLIDES

[http://www.santafe.edu/events/workshops/images/e/e7/Linear_algebra_tutorial.pdf Tutorial slides]

UPDATE! Time: Friday June 6th, 01.00 p.m. - 03.00 p.m. If this collides with other stuff, please yell out! [[CSSS 2008 Santa Fe-Schedule]]

Yes please. [[Kathleen_Sprouffske|Kathleen]]

I am also very interested [[Walter_Zesk|Walt]]

I'm in as well [[ Mark_Rivera|Mark]]

Please - have always been kind of confusing to me. [[Jonathan_Zelner|Jon]]

Let me in - Masayoshi

I'm also interested! [[ Flavia_Feitosa|Flavia]]

I'll be there. -[[Molly_Rorick|Molly]]

I'm in as well. -[[Tanja_Gesell|Tanja]]

Me too! '''Just to remind'''; I think Classical and Evolutionary Game Theory (Josh)will be started at 3 PM. Rio

== How your computer works ==

Nish and Laura can give a joint tutorial on 'how your computer works'. What happens when I type 'www.santafe.edu' in my browser? How does a web server at santafe.edu handle all those incoming requests? What happens when I use a WiFi access point? Basically, we'd be happy to take your questions about how your computer works and do our best to answer them - we're also happy to have other co-tutors.

Let us know if there's interest [mailto:lmfeeney@sics.se Laura], we'd probably schedule later next week, to not conflict with tutorials that focus on maths and other project prerequisites.

I would love this. -[[Sarah_Cobey|Sarah]]

== How your hardware works ==
Along the same lines as the computer tutorial, I've found myself discussing hardware with a number of folks. And why hardware matters from a massive parallelism perspective (which is quite common in the complex research areas I've encountered). If folks are interested, I can give a rough overview of the way hardware works in different types of computers and supercomputers (as much as I understand of it) as well as how to best leverage that knowledge.

Not sure how this differs from the the one above it, but def. interested (Chris)

== Computational Physics for Non-physicists or A small introduction into Applied Physics ==

I've seen that many people are interested in physics. I could give an introduction to "computational" physics - this means physics with a PC. Actually, it is very broad and gives some basics for simulations (interesting for all simulation-folks):

- What is a 'random number generator' and why should I know something about it?

- What are Master-equations?

- The Ising-model / Voter-model

- The Central Limit Theorem or why does it make sense to average over multiple runs of a simulation?

- ...

[[Ruben Kubiak|Ruben]]

I'm very interested [[Nish_Aravamudan|Nish]]

I'm in too. [[Jiang_Wu|Jiang]]

[[Srideep_Musuvathy|srideep]] is in.
Sounds great. [[Molly_Rorick|Molly]]

Looking forward to it. [[Petr Svarc|Petr]]

==Information Theory==
An open discussion of Shannon information theory (would like some help in presenting this part clearly) and then some newer results from its application to cellular automata (and potentially other complex systems).

Interesting. I remember something from the master course I took. [[User:Giovanni|Giovanni]] 
I'd love to participate. -[[Sarah_Cobey|Sarah]] 
I'm interested.[[Holger_Keeler|Paul]] 
I'm in. --[[User:Lfriedl|Lisa]]

I'm in. --[[User:meritxell|Meritxell]]

FYI: Tom Carter is going to be talking about Information Theory a bit tomorrow from 2-3pm, not sure of a location yet, but its on the schedule.

==Cellular Automata==
CAs (particularly ECAs) are a very interested model of computation. How do 8 rules (ECA 110, e.g.) emulate a Turing Machine? Why is that interesting? What can we learn about what defines computation given CAs? Maybe we can also discuss some simple computational (Turing) theory.

I'd go to that twice. —[[User:Jreyes|Josh]]

Sounds like fun. [[Christopher Vitale|Chris]]

==A little analytical tool-box: Non-linear dynamics, ODEs, PDEs...==
The [[David_Foster|Brothers]] [[Jacob_Foster|Foster]] would be happy to offer some tutorials on analytical methods. Depending on what Alfred Hubler covers, we can do some fraction of Strogatz (flows on the line & circle, bifurcations, maybe linear systems, index theorem, etc.), as well as offering a basic introduction to solving linear ODEs (no theorems, just techniques) and simple PDEs like the heat equation, with boundary conditions. Ideally this would come after Kolbjørn's eigen-stuff course, so we can just assume familiarity with that.

We've put a tentative time for our tutorial on the schedule: [[CSSS_2008_Santa_Fe-Schedule#Week_Three_-_FINANCE/ECONOMY|June 16 at 3:15pm]]. Let us know if this doesn't work out for some reason and we can try to change it.

These are fun topics! I never get enough of them! -- [[Srideep_Musuvathy|srideep]] 
Sounds great. [[Molly_Rorick|Molly]] 
Interesting -- sure. [[User:Lfriedl|Lisa]] 
Very useful! [[Kathleen_Sprouffske|Kathleen]] 
Need this.... Rio 
I'm in! [[Flavia_Feitosa|Flávia]]
great! [[Riley_Crane]]

Brothers Foster rulez! I'll be there. [[Petr Svarc|Petr]]

==Linguistics==
Can someone (I don't know [[Peter_Graff|who]]) perhaps offer a tutorial on basic linguistics stuff? I am particularly interested in generative grammar and coverage of the Chomsky "Three Models" paper, but maybe there are more interesting topics to be discussed these days... -Jacob

I could easily do a Saussure/Pierce tutorial, along with how this has been applied from everything to kinship structure to film theory to table manners, but this is continental structural linguistics, very diff from the chomsky stuff. I think Peter Graff can do the chomsky stuff, though, perhaps we could work on this together (Chris)

Would love both tutorials. Esp. the kinship structure stuff (is this Andre Weil's algebra chapter on kinship, from Levi-Strauss I think?) -Jacob

I'd love to participate. -Tanja

==Fitting models to data==
A few people have asked me for a brief review of fitting models to data, but I'd like to know what methods interest you. I could start with least squares and progress to Bayesian approaches, maximum likelihood, and some more recent developments in methods for exploring space (GAs, particle filters, MCMC) with which I'm familiar. I'm by no means an expert in all these topics, so please add your name below if there's something you'd like to learn about (a particular method or method for a particular context) or teach. I feel like this tutorial would be most appropriate for the third or fourth week. -[[Sarah_Cobey|Sarah]]

I am really interested in this. (Soumya)

cool [[Riley_Crane]]

==Networks, Sign Systems, and the Mind==

So, as an outgrowth of the (continental) theory/philosophy working group, I've come up with two ideas for tutorial/discussion sessions on stuff people might be interested in, in which I'd likely throw some materials at the group, then see where discussion takes us. The first one would be on theories of language and the mind. Probably start off with the first real theory of language and the brain, Freud's topological theory, and then move to how this was absorbed into structuralist linguistics/semiotics in the 1950's (Saussure's theory of signifiers, Jakobsen on axes of discourse, paradigms/syntagms, metaphoric value transfer, and how this was applied to kinship structures, social institutions, etc.) From there we could look at how Jacques Lacan built upon this with his 'mathemic' algebraic notation for discourse analysis. We could then look at how networked theories of mind challenge both the Lacanian model and its American counterparts (Fodor's psychosemantics, for example), particularly in regard to connectionist architectures in artificial neural networks, and how this leads to more distributed notions of linguistic structure. These new paradigms can allow us to move beyond notions of discrete 'signs' existing somewhere in the brain to models based on research in microfeature maps, dynamic network synchronization, spreading activation, and feature vectores. When synthesized with Lacan's insights, and blended with some ideas from object-relations theory and by thinkers like Marvin Minsky and Gerald Edelman, its possible to come up with models that actually reflect the impact of complex systems theories. Likely wayy too much stuff to squeeze in, but certainly enough to get a conversation going, even if we don't get to half of it!

Anyone interested? (-Chris)

== Questions at the Intersection of Neuroscience and Complexity ==

Update! This tutorial is scheduled for 10:30 AM Wedenesday (June 11), in the small library on the upper floor of Petersen student center, just behind the main conference room.

Related to Chris' proposal above, but perhaps on the flip side, I'd be happy to give a tutorial / lead a discussion on issues where questions of complexity intersect with problems in neuroscience. I'll distinguish this topic from the idea above, in that I'll focus a bit more on bottom-up questions rather than purely theory-motivated questions. Neuroscience is a very large field, so I'll talk about some of the things I know, but encourage others to bring their own knowledge and curiosity.

I'll start with a short background on neuroanatomy of humans and other species. Then I'll do a survey of what's sometimes termed "systems neuroscience". This is the branch of neuroscience that asks about behavior roughly on the level of neural circuits -- but which often jumps up and down scales, and overlaps pretty significantly with ideas in "cognitive neuroscience" where the focus is on a lot of the interesting, higher-order behaviors unique to relatively few species. Then I'll go over a couple of papers which I think start on a road to using complex systems. Examples of what I might talk about would be:

* [http://www.ncbi.nlm.nih.gov/pubmed/17428910?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum Kiani et al J. Neurophys 2007] '''Does the visual system naturally group objects into heirarchical categories?''' These authors tried to apply some dimensionality reduction techniques to neural data from monkey inferotemporal cortex. The ideas from Dr. Newman's lectures may be very appropriate here.
* [http://www.ncbi.nlm.nih.gov/pubmed/17660812?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum Assisi et al. Nature Neuroscience 2007] '''Sparseness in representation of odors'''. The Laurent lab has been combining high-quality experimental methods in the insect olfactory system with computational models (including network models) to look at how the insect system (and more recently the mammalian system) represent odors. The system presents a very interesting contrast to the visual system, in terms of the sparseness of representations at the early levels. There's some elegant circuitry mapped out here. '''BONUS QUESTION!''' I remember one of the questions they investigated earlier was how locusts transition from 'happy grasshopper' mode to 'Biblical swarm' mode. This has something to do with olfaction. This population behavior is probably a very intersting bifurcation; we can dig into what this reflects.
* [http://www.ncbi.nlm.nih.gov/pubmed/18047414?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum Machens and Brody, Neural Computation 2008]. [[http://www.molbio.princeton.edu/index.php?option=content&task=view&id=335 Carlos Brody]] does a lot of work on how neural circuits dynamics can allow for short term memory behavior. This includes comparing a perceived sensation to something you experienced a few seconds or minutes ago, and constructing an internal sense of how time elapses. His group uses tools like attractor networks to model this behavior.
* '''Walter Freeman's work'''. Freeman studies the mammalian visual system, but also has a background in talking about how neural circuits encode meaning. This will be an opportunity for me to go back and find some interesting results to discuss. We may also highlight the questions of information theory and oscillatory behavior in neural circuits, which covers researchers like Pascal Fries, John Huguenard, and David McCormick. I'll update this part with a more specific paper when I find a good one.

'''Timing?''' Right now I'll focus on Wednesday morning, June 11. Please let me know below if you're interested. If it's a small group we can meet in the small library next to the main room; this might encourage discussion. And of course, let me know if there's something within this area in which you're more or less interested.

Cheers, [[Rory_Sayres | Rory]]

I'll be there Wednesday AM. Teach me, oh wise Neuroscientist! [[Nish_Aravamudan|Nish]]

Hellsyeah. [[Christopher Vitale|Chris]]

==Network Economics and Value Theory==

So, for the third week of CSSS, I'm thinking of maybe doing a session on 'Network Economics and Value Theory' for whoever's interested. Likely start off with Marx's three levels of value (use, exchange, surplus), move to his theories on production, formulas for capital, commodity fetishism, sticky points of his famous 'labor theory of value,' then on to his analysis of modes of production, and his thesis on the falling rate of profit that was supposed to bring down capitalism (but which obviously didn't). From there we could discuss critiques/updates of this theory via the growth of Keynesianism/Stalinism/Neoliberalism, in order to get to David Harvey's new work on how neoliberal economies largely avoid demand crises by engineering carefully managed accumulation crises whose effects can be easily passed off to poorer nations using multi-national postwar institutions like the IMF/WTO. This leads to examples of how networked models can help us understand today's economic crises (for example, how evolutionary search models can help us understand the ways in which 'overleveraging' economies via 'market derivatives' can help funnel capital to hedge funds in rich countries). From there we could look at critiques of economic theories of value, particularly Deleuze and Guattari's notion of 'desiring-production' as that which links production of commodities to the production of consumers by the social unit of production, namely, the family, and how even this model needs to be rethought in terms of shifts in mass media. Other topics could include theories of network political activism, namely those of Hardt and Negri (Empire/Multitude) and Ernesto Laclau on social dislocations and crisis management via counterhegemonic blocs.

Anyone interested in any of this stuff, lemme know! (-Chris)

== Topological and Symbolic Dynamical Systems ==

I would like to address the perceived interest among [[Jacob_Foster|few]] of us here in topics relating to the topological dynamics and symbolic dynamics. I can talk a bit about ideas relating to the topological properties of dynamical systems and systems with very little structure to them (i.e., systems whose state spaces are merely a hausdorff space and a dynamic shift which is a continuous function). The symbolic dynamics part will deal with spaces of sequences of symbols and the dynamics being a shift map. I would like to wrap things up with a powerful tool - topological conjugacy - which allows us to define an 'equivalence' between two dynamical systems, one of which might be easier to understand and analyze. Ideally, this discussion will come after my topology tutorial, but I'll spend a few minutes describing formally and intuitively, the terms I use. Alternatively, we can form small discussion groups and chat about this over a cup of tea. [[Srideep_Musuvathy|srideep]]

absolutely interested. [[Christopher Vitale|Chris]]

== Economics & Finance 101 ==
A 1 hour mini crash-course on the basic principles of Economics and Finance. The aim of this tutorial is -hopefully- to give a heads up for the upcoming Economics/Finance week for people who do not have a background in Economics.
I will introduce 3 simple models of microeconomics, macroeconomics and finance that can give an idea of what economists do. [[Carlos_Yepez|Carlos]]

'''Date and time:''' Friday June 13, 3:00-4:00pm.

'''Note:''' Reply to this page if you are interested in taking this tutorial.
*[[Devin_Drown|Devin]

User:Sayres

2008-06-08T01:11:48Z

Drown:

=== Yay Redundancy! ===

My actual info is [[Rory_Sayres | here]].

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