Difference between revisions of "CSSS 2008 Santa Fe-Projects & Working Groups"
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Tentatively scheduled for 7pm -- [[Laura_Feeney|Laura]]
Tentatively scheduled for 7pm -- [[Laura_Feeney|Laura]]
=== Theory Group ===
=== Theory Group ===
Revision as of 19:45, 5 June 2008
|CSSS Santa Fe 2008|
- 1 Potential Projects
- 1.1 Antagonistic interspecific interactions
- 1.2 Biological Levels / Phenotypes Discussion
- 1.3 Something in Neuroscience
- 1.4 Asymetric co-evolution in space/time
- 1.5 Evolving skepticism
- 1.6 if you can't grow Collapse, you haven't explained it
- 1.7 Let's make networks secure
- 1.8 Network Security Concepts Inspired by Biological and Social Systems
- 1.9 Incorporating Data into Agent-Based Models
- 1.10 A Dance Evolution
- 1.11 Some ideas on modeling social media and on multi-agent modeling
- 1.12 Financial crisis in Housing Markets
- 2 Working Groups
- 3 BrainStorming 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)
- Impact of host heterogeneity (= consumer-resource dynamics with identity issues): (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 (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 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
- Let's discuss 6pm Thursday
- 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 effects 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
- Effects of pathogen competition on epidemic outbreaks
- Spatial heterogeneity of transmission of parasites
Infectious diseases: epidemic outbreaks vs. endemic steady states Direct vs. vector transmission of parasites/pathogens Non-genetic transmission of disease resistance
Interested? Please add ideas that you find interesting or would like to explore more (or just your name).
Epidemiology in general. -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!!
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 Carlos Brody at Princeton; another possibility is applying Network Theory to functional connectivity using some new MRI-based data methods (including 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. Sayres 18:34, 4 June 2008 (MDT)
Asymetric co-evolution in space/time
I would be interested studing dynamic networks that have different rates and/or distributions. You could think of a ecological interaction example of parasites that are distributed by wind and have a lifspan of a few weeks, and plants that are spatially contstraint and have an annual lifespan. Or a social-ecological example of people managing a certain natural resource.
I think there may be interesting connections between this problem and one of communication networks with different rates of data transmission and transceiver availability. So I would be intersted in discussing this; alternatively I would be happy to learn more about biology... -- Laura
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).
if you can't grow Collapse, you haven't explained it
Gared Diamond describes a five point framework for collapse of societies. These points are:
-resilience of the environment to human caused damage
-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.
I am also very interested in this Richard
Could we adapt this and include an urban perspective? Flávia
Everybody needs his physicist. :-) - Ruben
I'm interested in this project as well. Steve
I am interested! John
sounds fun. hope I can be of any help... 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.
- 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
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.
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
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.
- 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. (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: Steve
(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'
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.
- Is this really a complex system, or just something that is not transparent?
- What happens if the “Fed” had let Bear Stearns go bankrupt?
- What really caused our “crisis”?
Can this be modeled in terms of banks with different risk behaviors/practices?
Evolutionary Game Theory
A few of us were thinking that there wouldn't be enough time to discuss enough topics in EGT in a 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.
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 (Zhang2004). Maybe this could serve as inspiration for a project. (Flavia)
- I'm interested too. Kathleen
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.
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:
I'd also be interested in this. Tomorrow evening sounds good. Mark
Tentatively scheduled for 7pm -- Laura
Can we move at 6? I would like to attend Béla's tutorial ... Giovanni
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 morning, to avoid conflict with the hike on Saturday, specific time to be determined.
We've discussed several next steps, which I'll post after dinner :) --Hypothetical Hypochondriac
Non-equilibrium thermodynamics and the production of entropy
I brought with me the textbook "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
Emergence of language in an agent-based model
- I am still interested(Petr).
"Evolving" interactions in M.A.S. (See above my project ideas) Giovanni
Prediction in cultural markets
Time-horizon of political institutions for managing global environmental goods
Social network data/evolution of networks
Networks plus application of biological methods
Public goods gam, group cooperation, social network
Together with Qiqi(!?), some group behaviour / prediction-thing about CSSS 2008
gathering data from all us, including game theory(?) and perhaps agent based modeling
still brainstorming... join us!
- Epidemic models of depression/anxiety - Inference of stochastic models
Social-ecological system -> Resilience institutions
Emergence of segregation from a game theory perspective.
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?