Santa Fe Institute Events Wiki - User contributions [en]

Presentations 2012

2012-06-27T18:32:49Z

AHorn:

{{Complex Systems Summer School 2012}}

9:00 - 9:15: Christa Brelsford and Xin Lu: Changes in Social Network Structure in Response to Crisis: Using Twitter data to Explore the Effect of the Tōhoku Earthquake.

9:15 - 9:30: Piotr Milanowski and Georg F. Weber: Enzyme kinetics and the outcome of chemical reactions.

9:30 - 9:45: Fabio, Elena, Tom and Friederike: Collaboration in times of stress: an Agent Based Modelling approach

10:15 - 10:45: BREAK

10:45 - 11:00: Katrien, Jasmeen, Sandro, Cameron, Vanessa

11:15 - 11:30: Xue, Χλοε, Xiaoli

12:00 - 1:15: LUNCH

1:30 - 1:45: Xin and Abby

5:00: Final Remarks & Farewell Dinner

Complex Systems Summer School 2012-Project Presentations

2012-06-26T23:41:53Z

AHorn:

{{Complex Systems Summer School 2012}}

Use this space to post project presentations and outlines. Include group members, a brief outline, and your slides.

=== Price-time Dynamics of Contracts Traded on Prediction Markets ===

Joanne, Vikram, Matteo, Sanith

Prediction markets have been shown to outperform traditional methods of polls and opinion surveys in forecasting future events. The futures contracts traded in these markets assess the expectation of occurrence of a variety of events spread across multiple domains (political, economic, entertainment, financial and weather). We explore the feasibility of 'predicting' the outcome of binary true/false prediction market contracts ahead of their expiry date using a neural-network based machine learning approach. In addition we focus on the characteristics of political-based contracts to establish whether they exhibit characteristic 'fundamental' properties.

=== How Complex Languages Replicate through Simple Brains ===

Katrien, Vanessa, Sandro, Cameron, Jasmeen

Through the use of an iterated learning experiment, we investigated the transmission of a "high entropy", randomised initial language through successive generations of participants. We want to see what features of the language replicated most easily, and what structure emerged by the end of the chain. Our hypothesis is that the language converges to a "low entropy" equilibrium state with a minimal number of words, morphemes, and form-meaning distinctions.

=== Collaboration in times of stress: an Agent Based Modelling approach ===

Fabio Cresto Aleina, Elena del Val, Tom Fennewald and Friederike Greb

We want to investigate the influence of exogenous stress on cooperative behaviour. We propose an agent based model in which the agents can be interpreted as farmers living in a water limited environment. With changes in precipitation patterns, the farmers undergo stress, and we observe how this impacts relationships among farmers and their properties.

=== Simple variation of the logistic map as a model to invoke questions on cellular protein trafficking ===
(Sepehr Ehsani, http://arxiv.org/abs/1206.5557)

Many open problems in biology, as in the physical sciences, display nonlinear and 'chaotic' dynamics, which, to the extent possible, cannot be reasonably understood. Moreover, mathematical models which aim to predict/estimate unknown aspects of a biological system cannot provide more information about the set of biologically meaningful (e.g., 'hidden') states of the system than could be understood by the designer of the model ab initio. Here, the case is made for the utilization of such models to shift from a 'predictive' to a 'questioning' nature, and a simple natural-logarithm variation of the logistic polynomial map is presented that can invoke questions about protein trafficking in eukaryotic cells.

===Changes in Social Network Structure in Response to Crisis: Using Twitter data to Explore the Effect of the Tōhoku Earthquake.===

Christa Brelsford and Xin Lu

Abstract:
We use twitter data from 7 days before and after the Tōhoku Earthquake to explore how cooperation rates, social network structure and connectivity, and social network vulnerability changed in Japan in response to the disaster. An English language data set is collected for the same time period to use as a control. Data is collected for a period of 96 hours starting from March 4th 2011 2:46pm JST and for 96 hours beginning March 11th 2011 2:46 pm JST. The rate of cooperative behavior, measured by the occurrence of helping words in tweets increases slightly in the English dataset and by an order of magnitude in the Japanese dataset. A network analysis is also performed. Network edges are retweets and direct messages. In future work, we hope to explore whether problem solving capacity in a social system changes in response to crises, based on changes in the rate of cooperation and information transfer in a network.

=== The CSSS Network ===

Tom & Riccardo (with JP and others)

We will investigate the questions you are dying to know: What interesting interactions are revealed from the first 3 weeks of the Complex System Summer School survey? Have barriers between academic disciplines been broken down? Do power laws fit the data!? ...

Let us know if you have specific questions or if you would like to be involved in data analysis!

=== Is there a method in the madness? the dynamic structures of human language use ===

Priya and Riccardo

Psychiatric anecdotal reports point to the monotony, lack of emotion and sometimes intelligibility in many clinical populations. Linear measures of fluency and prosody, however, present only controversial differences between patients and healthy controls and only in unnatural phonations (i.e. say "aaaaa" for 30 secs).
We therefore go complex and chaotic on a set of more ecological recordings and transcriptions from 4 clinical populations (Asperger's, Schizophrenics, Depressed and Right Hemisphere Damage patients) as well as from healthy controls.
We then set a classifier-driven race: will non-linear analyses outcompete linear analyses in discriminating between pathologies?

=== Escaping the Poverty Trap: Modeling the Interplay Between Economic Growth and the Ecology of Infectious Disease ===

Georg, Ben, Laurent, Oscar

The dynamics of economies and infectious disease are inexorably linked: economic well-being influences health (sanitation, nutrition, etc) and health influences economic well-being (labor productivity lost to sickness and disease). Often societies are locked into "poverty traps" of poor health and poor economy. Here, we demonstrate poverty traps formed in models of infection and endogenous growth, as well as ways to break out of poverty traps. We explore two mechanisms of escape: one, through an influx of capital, and another through changing the percentage of GDP spent on healthcare. We find large influxes of capital is successful, but increasing health spending does not. Our results have important policy implications in the distribution of aid and within-country healthcare spending.

=== The Targeting and Timing of Treatment Influences the Emergence of Influenza Resistance in Structured Populations ===

Ben, Laurent, Oscar, Georg

Evolution of antiviral resistance in influenza carries large societal impacts through morbidity and mortality caused by treatment failure. Several previous studies put forth theory regarding the optimal timing, targeting and absolute level of treatment in populations. Few of these studies, however, have considered populations with explicit structure. Here we present a model of antiviral resistance on networks and explore the timing, targeting and levels of treatment. Interestingly, we find bistability as a result of treatment leading to the existence of an unstable manifold, above which successful treatment (i.e.: no resistance) is impossible. We find, contrary to previous results, that degree-targeted treatment is not optimal, and leads to higher levels of resistance than random treatment. Additionally, in accordance with previous results, we find an optimum level of treatment which is less than 100%. These findings findings have important consequences in guiding policy behind influenza treatment. The bistability indicates that caution should be taken when treating populations when the absolute numbers of infections are unknown. Positively, our results indicate that putting resources into targeted treatment is not necessary, random treatment is preferable.

=== Learning in Random Boolean Networks ===

Nick A., Keegan, Matteo, Vikram, Sarah, Mark

Inspired by biochemical networks which adapt on evolutionary timescales, neural networks that adapt during development and learning, and universal computation in cellular automata, we have implemented several models of learning in Random Boolean Networks (RBNs) in order to better understand the relationships between network structure, node interaction rules, and network output.

=== Enzyme Catalysis and the Outcome of Chemical Reactions ===
Piotr and Georg W.
Enzymes are catalysts that accelerate chemical reactions but do not affect their outcome. This traditional paradism was developed under artificail test tube conditions. Our project investigates the possibility that the presence of an enzyme can alter the course of a reaction if it takes place under more physiologic conditions.

=== How Does a Network’s Structure Influence its Traceability? ===

Xin and Abby

We are interested in systematically studying the problem of finding the source of a contamination spread through a network. We model a contamination spreading through the food distribution network, which we represent by interconnections between farmers, distributors, and retailers, and construct an estimator for the outbreak source given only this structure. We show how the ability of the estimator to narrow down the source identification problem changes with the connectivity and the number of observations. We propose a measure for traceability, or the overall ability to identify the source of spreading given any set of outbreak observations, based on entropy. We show how this measure appropriately reflects the range of uncertainty in identifying the source. We believe this measure may be useful in the design of networks that are conducive to accurate identification of the source of contamination.

Experiment sign-up

2012-06-18T03:20:14Z

AHorn: /* Monday June 18 */

Hi! Please sign up for one slot below. The experiment will be held in the Senior Common Room (JP's office) next to the great hall. Please arrive on time!

- Katrien, Vanessa, Sandro, Cameron & Jasmeen

==Monday June 18==

Morning Break:

9.30-9.40: Ryan

9.40-9.50: Benji

9.50-10.00: Friederike

10.00-10.10: Oscar

10.10-10.20: Tom

10.20-10.30: Piotr

10.30-10.40: Laurent

Lunch Break:

12.05-12.15: Chloe

12.15-12.25: Andres

12.25-12.35: Xue

12.35-12.45: Oleksandr

12.55-1.05: Nick A

1.05-1.15: Fabio

1.15-1.25: Priya

Afternoon:

4.30-4.40: Matteo

4.40-4.50:Ben

4.50-5.00: Sarah

5.00-5.10: Charlie

5.10-5.20: Abby

5.20-5.30:

5.30-5.40:

5.40-5.50:

5.50-6.00:

6.00-6.10:

6.10-6.20:

6.20-6.30:

6.30-6.40:

6.40-6.50:

6.50-7.00:

Complex Systems Summer School 2012-Tutorials

2012-06-15T22:03:25Z

AHorn: /* Markov Chain Monte Carlo */

{{Complex Systems Summer School 2012}}

CSSS participants come from a wide range of disciplines. Participants are encouraged to share their knowledge by organizing their own tutorials.

Also, please post requests for tutorials here.

==Markov Chain Monte Carlo==
If anyone is interested in talking more about Bayesian methods and MCMC implementation, I'd be happy to put something together. - Keegan

-Hide is interested in this!

-Abby

==Python, Computational Mechanics, and Information Theory==

There has been interest in more discussion on a number of topics, and so i'm offering to have evening discussions on them. please sign up below so that i can get a feel for the number of people who would be attending. also, please put a preference for what day it should be.

===Python===
Sign up below if you'd like an introduction to basic python programming. Python is a general purpose, very flexible and useful programming language. It is used pretty extensively in scientific computing.

dan wu: wu12345@gmail.com Let me know when we're meeting

- Benji: bzusman@gmail.com 

-Keegan keegan.hines@gmail.com

-Christa (maybe- I'm competent at the very basics, but could still use some help)

- Riccardo: fusaroli@gmail.com

- Oleksandr: krystoferivanov@gmail.com

- Nona: nona.karalashvili@gmail.com

- Xiaoli: xiaolidong2008@gmail.com

- Abby: Abbyhorn@Mit.edu

- Marco: maduenase@gmail.com

- Nick: goudemand at pim dot uzh dot ch

- Joanne: joannerodrigues@berkeley.edu

- Hide: hi55 at cornell dot edu

- Priya: iitm.priya@gmail.com

- Miguel: miguel.lurgi@icm.csic.es

- Oscar: opatters@asu.edu

===Information Theory===
Interested in turning your data into bits, or seeing how the bits over there are related to the bits over here? If so, sign up below. 
- Matteo

- Benji: bzusman@gmail.com

-Keegan keegan.hines@gmail.com

-Riccardo

-Christa

- Katrien

- Xiaoli

- Abby

- Jasmeen

- Hide

- Sanith

- Priya

- Georg W.

- Piotr

- Miguel

- Oscar
===Computational Mechanics===
If you'd like to know more about epsilon machines, measures of complexity, how to go from a map to a machine, i'm happy to discuss it all. 
- Matteo

Yes please! --Chloe

-Keegan keegan.hines@gmail.com

-Christa

-Xiaoli

-Jasmeen

-Hide

-Sanith

- Priya

- Georg W.

-Piotr

-Ian

- Miguel

- Oscar

- Abby

==Order Book Dynamics: Learn how to trade in 15min==

--I'm happy to repeat this -just get in touch with me.--

If you are curious about how stocks trade and want to try your luck, I'll
be going over some of the basics with a hands-on example.

Meet at 7.30pm in main lecture hall Thursday June 7th. Please make sure
to bring your laptop.

Sanith

==Update==

Hi guys

I guess the mail lecture hall is free at 6.30 pm and so we can meet there. I have a small talk through the idea and then maybe we can try out getting bifurcation plots for one or two systems. I use software written in MATLAB for the demo but the idea can be implemented in any software.

Here's a link to the [[software for numerical continuation|http://twr.cs.kuleuven.be//research/software/delay/notice.shtml]]. This software can handle systems with time delays and can be used to obtain the bifurcation behaviour.

(1) Please download the software DDE-BIFTOOL and unzip.

(2) Within the folder, you will find another zipped folder in small case ‘ddebiftool’. Please unzip this into a folder with the same name

(3) Add the location of the folder to the path of MATLAB.
I have also sent out a mail with a zipped folder containing files to get a bifurcation plot for a Rijke tube system.
Do let me know if anyone did not get this.
See you there!

Priya

==An easier way to get a bifurcation plot==

Hey guys
I have been working in the past in obtaining bifurcation plots for different physical systems. There's a better way to get these pictures instead of getting the evolution at every parameter value of interest. This is called ''numerical continuation'' and basically involves tracking a curve. I plan to give a informal talk on how to do this and maybe even a demo on applying this technique on 14th June at 6.30 pm. Do mail me if you are interested at '''iitm.priya@gmail.com''' or sign up below.
[[User:Priya|Priya]]

- [[Ryan James|Ryan]] is interested in this. 
- Riccardo is interested in this. 
- Vikram is interested in this. 
- Matteo is interested in this. 
- Hide is interested in this. 
- Katrien wants to hear more about this. 
- Cameron is interested in this and would like to see [http://itunes.apple.com/us/app/xpp/id433859546?mt=8 this] in action if anyone has an iPad. 
- Oscar is interested in this. 
- Charlie is interested in this. (I've done this once for a paper.) 
- Georg W. is interested in this 

==Using Tisean on R on OS X==
first install TISEAN, like you've done already. Make sure R is up to date (v 2.15).
you can try to install RTisean from CRAN
install.packages("RTisean"); library(RTisean); henon()
But me and Dave both got an error about some bad file name, something about con and something about a long path involving -Tmp-
Solution:
remove.packages("RTisean")
restart R
download this: http://cl.ly/0I0b2P2L311y1q0q0y0n
install it, it changes line 74 of nativeTISEAN.R which has some problems with file handling
If you are golden, then:
> henon()
V1 V2
[1,] -0.1232481 -1.030383

Complex Systems Summer School 2012-Tutorials

2012-06-15T05:26:37Z

AHorn: /* Computational Mechanics */

{{Complex Systems Summer School 2012}}

CSSS participants come from a wide range of disciplines. Participants are encouraged to share their knowledge by organizing their own tutorials.

Also, please post requests for tutorials here.

==Python, Computational Mechanics, and Information Theory==

There has been interest in more discussion on a number of topics, and so i'm offering to have evening discussions on them. please sign up below so that i can get a feel for the number of people who would be attending. also, please put a preference for what day it should be.

===Python===
Sign up below if you'd like an introduction to basic python programming. Python is a general purpose, very flexible and useful programming language. It is used pretty extensively in scientific computing.

dan wu: wu12345@gmail.com Let me know when we're meeting

- Benji: bzusman@gmail.com 

-Keegan keegan.hines@gmail.com

-Christa (maybe- I'm competent at the very basics, but could still use some help)

- Riccardo: fusaroli@gmail.com

- Oleksandr: krystoferivanov@gmail.com

- Nona: nona.karalashvili@gmail.com

- Xiaoli: xiaolidong2008@gmail.com

- Abby: Abbyhorn@Mit.edu

- Marco: maduenase@gmail.com

- Nick: goudemand at pim dot uzh dot ch

- Joanne: joannerodrigues@berkeley.edu

- Hide: hi55 at cornell dot edu

- Priya: iitm.priya@gmail.com

- Miguel: miguel.lurgi@icm.csic.es

- Oscar: opatters@asu.edu

===Information Theory===
Interested in turning your data into bits, or seeing how the bits over there are related to the bits over here? If so, sign up below. 
- Matteo

- Benji: bzusman@gmail.com

-Keegan keegan.hines@gmail.com

-Riccardo

-Christa

- Katrien

- Xiaoli

- Abby

- Jasmeen

- Hide

- Sanith

- Priya

- Georg W.

- Piotr

- Miguel

- Oscar
===Computational Mechanics===
If you'd like to know more about epsilon machines, measures of complexity, how to go from a map to a machine, i'm happy to discuss it all. 
- Matteo

Yes please! --Chloe

-Keegan keegan.hines@gmail.com

-Christa

-Xiaoli

-Jasmeen

-Hide

-Sanith

- Priya

- Georg W.

-Piotr

-Ian

- Miguel

- Oscar

- Abby

==Order Book Dynamics: Learn how to trade in 15min==

--I'm happy to repeat this -just get in touch with me.--

If you are curious about how stocks trade and want to try your luck, I'll
be going over some of the basics with a hands-on example.

Meet at 7.30pm in main lecture hall Thursday June 7th. Please make sure
to bring your laptop.

Sanith

==Update==

Hi guys

I guess the mail lecture hall is free at 6.30 pm and so we can meet there. I have a small talk through the idea and then maybe we can try out getting bifurcation plots for one or two systems. I use software written in MATLAB for the demo but the idea can be implemented in any software.

Here's a link to the [[software for numerical continuation|http://twr.cs.kuleuven.be//research/software/delay/notice.shtml]]. This software can handle systems with time delays and can be used to obtain the bifurcation behaviour.

(1) Please download the software DDE-BIFTOOL and unzip.

(2) Within the folder, you will find another zipped folder in small case ‘ddebiftool’. Please unzip this into a folder with the same name

(3) Add the location of the folder to the path of MATLAB.
I have also sent out a mail with a zipped folder containing files to get a bifurcation plot for a Rijke tube system.
Do let me know if anyone did not get this.
See you there!

Priya

==An easier way to get a bifurcation plot==

Hey guys
I have been working in the past in obtaining bifurcation plots for different physical systems. There's a better way to get these pictures instead of getting the evolution at every parameter value of interest. This is called ''numerical continuation'' and basically involves tracking a curve. I plan to give a informal talk on how to do this and maybe even a demo on applying this technique on 14th June at 6.30 pm. Do mail me if you are interested at '''iitm.priya@gmail.com''' or sign up below.
[[User:Priya|Priya]]

- [[Ryan James|Ryan]] is interested in this. 
- Riccardo is interested in this. 
- Vikram is interested in this. 
- Matteo is interested in this. 
- Hide is interested in this. 
- Katrien wants to hear more about this. 
- Cameron is interested in this and would like to see [http://itunes.apple.com/us/app/xpp/id433859546?mt=8 this] in action if anyone has an iPad. 
- Oscar is interested in this. 
- Charlie is interested in this. (I've done this once for a paper.) 
- Georg W. is interested in this 

==Using Tisean on R on OS X==
first install TISEAN, like you've done already. Make sure R is up to date (v 2.15).
you can try to install RTisean from CRAN
install.packages("RTisean"); library(RTisean); henon()
But me and Dave both got an error about some bad file name, something about con and something about a long path involving -Tmp-
Solution:
remove.packages("RTisean")
restart R
download this: http://cl.ly/0I0b2P2L311y1q0q0y0n
install it, it changes line 74 of nativeTISEAN.R which has some problems with file handling
If you are golden, then:
> henon()
V1 V2
[1,] -0.1232481 -1.030383

Complex Systems Summer School 2012-Tutorials

2012-06-13T21:49:25Z

AHorn: /* Information Theory */

{{Complex Systems Summer School 2012}}

CSSS participants come from a wide range of disciplines. Participants are encouraged to share their knowledge by organizing their own tutorials.

Also, please post requests for tutorials here.

==Python, Computational Mechanics, and Information Theory==

There has been interest in more discussion on a number of topics, and so i'm offering to have evening discussions on them. please sign up below so that i can get a feel for the number of people who would be attending. also, please put a preference for what day it should be.

===Python===
Sign up below if you'd like an introduction to basic python programming. Python is a general purpose, very flexible and useful programming language. It is used pretty extensively in scientific computing.

dan wu: wu12345@gmail.com Let me know when we're meeting

- Benji: bzusman@gmail.com 

-Keegan

-Christa (maybe- I'm competent at the very basics, but could still use some help)

-Riccardo

- Oleksandr: krystoferivanov@gmail.com

- Nona: nona.karalashvili@gmail.com

- Xiaoli: xiaolidong2008@gmail.com

- Abby: Abbyhorn@Mit.edu

===Information Theory===
Interested in turning your data into bits, or seeing how the bits over there are related to the bits over here? If so, sign up below. 
- Matteo

- Benji: bzusman@gmail.com

-Keegan

-Riccardo

-Christa

- Katrien

- Xiaoli

- Abby

===Computational Mechanics===
If you'd like to know more about epsilon machines, measures of complexity, how to go from a map to a machine, i'm happy to discuss it all. 
- Matteo

Yes please! --Chloe

-Keegan

-Christa

-Xiaoli

==Order Book Dynamics: Learn how to trade in 15min==

--I'm happy to repeat this -just get in touch with me.--

If you are curious about how stocks trade and want to try your luck, I'll
be going over some of the basics with a hands-on example.

Meet at 7.30pm in main lecture hall Thursday June 7th. Please make sure
to bring your laptop.

Sanith

==An easier way to get a bifurcation plot==

Hey guys
I have been working in the past in obtaining bifurcation plots for different physical systems. There's a better way to get these pictures instead of getting the evolution at every parameter value of interest. This is called ''numerical continuation'' and basically involves tracking a curve. I plan to give a informal talk on how to do this and maybe even a demo on applying this technique on 14th June at 6.30 pm. Do mail me if you are interested at '''iitm.priya@gmail.com''' or sign up below.
[[User:Priya|Priya]]

- [[Ryan James|Ryan]] is interested in this. 
- Riccardo is interested in this. 
- Vikram is interested in this. 
- Matteo is interested in this. 
- Hide is interested in this. 
- Katrien wants to hear more about this. 
- Cameron is interested in this and would like to see [http://itunes.apple.com/us/app/xpp/id433859546?mt=8 this] in action if anyone has an iPad. 
- Oscar is interested in this. 
- Charlie is interested in this. (I've done this once for a paper.) 

==Using Tisean on R on OS X==
first install TISEAN, like you've done already. Make sure R is up to date (v 2.15).
you can try to install RTisean from CRAN
install.packages("RTisean"); library(RTisean); henon()
But me and Dave both got an error about some bad file name, something about con and something about a long path involving -Tmp-
Solution:
remove.packages("RTisean")
restart R
download this: http://cl.ly/0I0b2P2L311y1q0q0y0n
install it, it changes line 74 of nativeTISEAN.R which has some problems with file handling
If you are golden, then:
> henon()
V1 V2
[1,] -0.1232481 -1.030383

Complex Systems Summer School 2012-Tutorials

2012-06-13T21:47:56Z

AHorn: /* Python */

{{Complex Systems Summer School 2012}}

CSSS participants come from a wide range of disciplines. Participants are encouraged to share their knowledge by organizing their own tutorials.

Also, please post requests for tutorials here.

==Python, Computational Mechanics, and Information Theory==

There has been interest in more discussion on a number of topics, and so i'm offering to have evening discussions on them. please sign up below so that i can get a feel for the number of people who would be attending. also, please put a preference for what day it should be.

===Python===
Sign up below if you'd like an introduction to basic python programming. Python is a general purpose, very flexible and useful programming language. It is used pretty extensively in scientific computing.

dan wu: wu12345@gmail.com Let me know when we're meeting

- Benji: bzusman@gmail.com 

-Keegan

-Christa (maybe- I'm competent at the very basics, but could still use some help)

-Riccardo

- Oleksandr: krystoferivanov@gmail.com

- Nona: nona.karalashvili@gmail.com

- Xiaoli: xiaolidong2008@gmail.com

- Abby: Abbyhorn@Mit.edu

===Information Theory===
Interested in turning your data into bits, or seeing how the bits over there are related to the bits over here? If so, sign up below. 
- Matteo

- Benji: bzusman@gmail.com

-Keegan

-Riccardo

-Christa

- Katrien

- Xiaoli

===Computational Mechanics===
If you'd like to know more about epsilon machines, measures of complexity, how to go from a map to a machine, i'm happy to discuss it all. 
- Matteo

Yes please! --Chloe

-Keegan

-Christa

-Xiaoli

==Order Book Dynamics: Learn how to trade in 15min==

--I'm happy to repeat this -just get in touch with me.--

If you are curious about how stocks trade and want to try your luck, I'll
be going over some of the basics with a hands-on example.

Meet at 7.30pm in main lecture hall Thursday June 7th. Please make sure
to bring your laptop.

Sanith

==An easier way to get a bifurcation plot==

Hey guys
I have been working in the past in obtaining bifurcation plots for different physical systems. There's a better way to get these pictures instead of getting the evolution at every parameter value of interest. This is called ''numerical continuation'' and basically involves tracking a curve. I plan to give a informal talk on how to do this and maybe even a demo on applying this technique on 14th June at 6.30 pm. Do mail me if you are interested at '''iitm.priya@gmail.com''' or sign up below.
[[User:Priya|Priya]]

- [[Ryan James|Ryan]] is interested in this. 
- Riccardo is interested in this. 
- Vikram is interested in this. 
- Matteo is interested in this. 
- Hide is interested in this. 
- Katrien wants to hear more about this. 
- Cameron is interested in this and would like to see [http://itunes.apple.com/us/app/xpp/id433859546?mt=8 this] in action if anyone has an iPad. 
- Oscar is interested in this. 
- Charlie is interested in this. (I've done this once for a paper.) 

==Using Tisean on R on OS X==
first install TISEAN, like you've done already. Make sure R is up to date (v 2.15).
you can try to install RTisean from CRAN
install.packages("RTisean"); library(RTisean); henon()
But me and Dave both got an error about some bad file name, something about con and something about a long path involving -Tmp-
Solution:
remove.packages("RTisean")
restart R
download this: http://cl.ly/0I0b2P2L311y1q0q0y0n
install it, it changes line 74 of nativeTISEAN.R which has some problems with file handling
If you are golden, then:
> henon()
V1 V2
[1,] -0.1232481 -1.030383

Complex Systems Summer School 2012-After Hours

2012-06-13T21:46:32Z

AHorn: /* Trip to Abiquiu */

{{Complex Systems Summer School 2012}}

Use this space to organize your own after hours activities.

==Dancing==
Of particular varieties --

There's a contra on the 23rd; swing dancing most Mondays; this is supposed to be a great tango town, and I'm looking for drop-in-friendly beginner classes...

[http://www.santafenewmexican.com/Sidebar/Dance_fever_in_Santa_Fe swing, salsa, tango]

[http://www.folkmads.org/may_jun_calendar12.html contras, here and ABQ]

We've heard great Appalachian-style folk musicians here already, but I haven't found a ceili or hoedown locally.

--Chloe

==Trip to Abiquiu==

We are organizing a trip to lake Abiquiu this weekend. Google maps says it should take about 1:10 hour driving from Santa Fe. Who's interested? We'll have to rent cars to go there.

Fabio

Friederike

Elena

Mikkel

John

Nona

Abby

==Saturday Football==

Who is up for a quick match tomorrow at 8am before the Bandelier trip? Let's make it a relaxed, just-for-fun match. Sign up below:

- [[Miguel Lurgi|Miguel]]

==Bandelier Field Trip==

Bandelier Field Trip
Trip to Bandelier National Monument on Sat. June 9.
We might string a visit to the Valles Caldera and Bradbury Science Museum/Los Alamos in as well. If another group would like to stay around Bandelier, we can split up.

Head over to the [[Bandelier Trip 2012 | Bandelier Trip]] Page to sign up!

==Mafia==

[[JP]] is a huge fan of Mafia/Werewolf. Let's play a game sometime in the lower commons.

Let's meet Saturday evening at 8:00 in the lower commons for our first game.

- [[Ryan_James|Ryan]] is down for this.

- Jasmeen is also a big fan of Mafia.

- Ian has never played, but is interested

- Vikram is interested in learning the game.

- Tom F. would like to join and can also teach "The Resistance" a very similar game

- Katrien wants to play too

==FOOTBALL!==

Anyone up for a friendly game of soccer? We can check out equipment from the gym.

[Team: Continuous!] 
1. [[Piotr Milanowski|Piotr]] 
2. [[Marco Duenas|Marco]] 
3.[[Oleksandr Ivanov|Alex]] 
4. 
5. 
[Team: Discrete!] 
1. [[Fabio Cresto Aleina|Fabio]] 
2. [[Matteo Chinazzi|Matteo]] 
3.[[JP]] 
4. 
5.

Robustness of complex networks (project)

2012-06-12T05:13:12Z

AHorn: /* Participants */

[[File:Zoo.png|thumb|300px|Fig. 1. Zoo of complex networks (an example). Taken from Sol´e and Valverde, 2001.]]
== Problem statement ==
Complex networks have various properties which can be measured in real networks (WWW, social networks, biological networks), e.g. degree distribution, modularity, hierarchy, assortativity etc. Robustness of complex networks is a big question, however only some progress have been done in this direction. For example, it was shown that the scale-free networks are much more topologically robust to random attacks than random networks. Many people claim that various characteristics of complex networks will influence the robustness interdependently. The question I am interested in is how?

== Approach ==
The idea is to generate continuous topology space of various complex networks (networks with different modularity, degree distribution, hierarchy etc) and use it to measure their robustness (see Fig. 1). There are many approaches to measure the robustness of complex networks. For example we can remove edges of vertices of a complex network graph and look at the size of a giant cluster. We can discuss other possibilities.

If you are interested you can contact me directly or via my E-mail: krystoferivanov@gmail.com or via my [[Oleksandr Ivanov|discussion page in CSSS 2012 wiki]].

== Relevant literature ==
* ''Important papers about network generation are highlighted in bold''
* '''[http://www.barabasilab.com/pubs/CCNR-ALB_Publications/199910-15_Science-Emergence/199910-15_Science-Emergence.pdf BA Scale-free network]'''
* '''[http://people.maths.ox.ac.uk/maini/PKM%20publications/195.pdf How to generate Scale-free modular network using preferential attachment]'''
* '''[http://arxiv.org/pdf/cond-mat/0402009v1.pdf Scale-free networks with tunable degree distribution exponents]'''
* '''[http://arxiv.org/pdf/cond-mat/0110452v1.pdf Scale free networks with tunable clustering]'''
* [http://www.barabasilab.com/pubs/CCNR-ALB_Publications/200007-27_Nature-ErrorAttack/200007-27_Nature-ErrorAttack.pdf Error and attack tollerance of complex networks]
* [http://vw.indiana.edu/netsci06/conference/Ng_Structural.pdf Structural Robustness of Complex networks]
* [http://arxiv.org/pdf/cond-mat/0205405.pdf Assortative mixing in networks]
* [http://www.cis.upenn.edu/~mkearns/teaching/NetworkedLife/prefatt.pdf Mean field theory to study scale-free networks]
* [http://www.graphanalysis.org/SIAM-PP08/Leskovic.pdf Kroneker Graphs]
* [http://www.lem.sssup.it/WPLem/files/2011-07.pdf Exact maximum-likelihood method to detect patterns in real networks]
* [http://www-users.york.ac.uk/~lsdc1/SysBiol/kitano.robustness.naturegenetics.2004.pdf Biological robustness]
* [http://arxiv.org/ftp/cond-mat/papers/0202/0202410.pdf Attack vulnerability of complex networks]
* [http://jmvidal.cse.sc.edu/papers/nair11a.pdf Supply Network Topology and Robustness against Disruptions – an investigation using multi agent model]

* [http://arxiv.org/abs/cond-mat/0007235 Random graphs with arbitrary degree distributions and their applications]
* [http://www.pnas.org/content/104/1/36 Resolution limit in community detection] - about a typical modularity measure and its limitations

* Add a relevant paper...

== Learning Python ==
* [http://code.google.com/edu/languages/google-python-class/ Google's Python Class]
* [http://networkx.lanl.gov/tutorial/tutorial.html Networkx Python lybrary]
* [http://networkx.lanl.gov/reference/algorithms.html Networkx graph algorithms]
* [http://networkx.lanl.gov/reference/drawing.html Networkx drawing]

== Participants ==
# [[Oleksandr Ivanov]] - krystoferivanov@gmail.com
# [[Ian Wood]] - ibwood@indiana.edu
# [[Xin Lu]] - xin.lu@ki.se
# [[Duenas-Esterling Marco-Antonio]] - maduenase@gmail.com
# [[Katrien Beuls]] - katrien@ai.vub.ac.be
# [[Cameron Ray Smith]] - [http://www.google.com/recaptcha/mailhide/d?k=01_G1kMsuOrJhiwcXbYs5uYQ==&c=4iKaQQLKYQ-uUaepLzz3_1LdZfwZMM24y5sG4GTjP-4= c...@gmail.com]
# [[Abigail Horn]] - abbyhorn@mit.edu


== Source Control ==
I've set up a github repository for any python source we write [https://github.com/ibwood/CSSS-Network-Robustness-Project here].
To figure out how to use Git look [http://git-scm.com/book here]. Chapters 1,2,3, and 5 are particularly relevant, but I can run through the basics with anyone. It's useful to have a source control for both project coordination and backup, and git is very simple once you get the hang of it.

There is a shared folder on skype, please either sign your email in the participant list or drop a email to [[Xin Lu]] to access the generated network data. Dropbox link [https://www.dropbox.com/sh/y6e5ukftde4yt7x/i4ZZ03Yr_5]

== BA algorithm in Python ==
* [http://networkx.lanl.gov/_modules/networkx/generators/random_graphs.html#barabasi_albert_graph Networkx source]

== BA network + modularity ==
* [http://networkx.lanl.gov/_modules/networkx/generators/random_graphs.html#powerlaw_cluster_graph Networkx source]

Robustness of complex networks (project)

2012-06-12T05:12:42Z

AHorn: /* Participants */

[[File:Zoo.png|thumb|300px|Fig. 1. Zoo of complex networks (an example). Taken from Sol´e and Valverde, 2001.]]
== Problem statement ==
Complex networks have various properties which can be measured in real networks (WWW, social networks, biological networks), e.g. degree distribution, modularity, hierarchy, assortativity etc. Robustness of complex networks is a big question, however only some progress have been done in this direction. For example, it was shown that the scale-free networks are much more topologically robust to random attacks than random networks. Many people claim that various characteristics of complex networks will influence the robustness interdependently. The question I am interested in is how?

== Approach ==
The idea is to generate continuous topology space of various complex networks (networks with different modularity, degree distribution, hierarchy etc) and use it to measure their robustness (see Fig. 1). There are many approaches to measure the robustness of complex networks. For example we can remove edges of vertices of a complex network graph and look at the size of a giant cluster. We can discuss other possibilities.

If you are interested you can contact me directly or via my E-mail: krystoferivanov@gmail.com or via my [[Oleksandr Ivanov|discussion page in CSSS 2012 wiki]].

== Relevant literature ==
* ''Important papers about network generation are highlighted in bold''
* '''[http://www.barabasilab.com/pubs/CCNR-ALB_Publications/199910-15_Science-Emergence/199910-15_Science-Emergence.pdf BA Scale-free network]'''
* '''[http://people.maths.ox.ac.uk/maini/PKM%20publications/195.pdf How to generate Scale-free modular network using preferential attachment]'''
* '''[http://arxiv.org/pdf/cond-mat/0402009v1.pdf Scale-free networks with tunable degree distribution exponents]'''
* '''[http://arxiv.org/pdf/cond-mat/0110452v1.pdf Scale free networks with tunable clustering]'''
* [http://www.barabasilab.com/pubs/CCNR-ALB_Publications/200007-27_Nature-ErrorAttack/200007-27_Nature-ErrorAttack.pdf Error and attack tollerance of complex networks]
* [http://vw.indiana.edu/netsci06/conference/Ng_Structural.pdf Structural Robustness of Complex networks]
* [http://arxiv.org/pdf/cond-mat/0205405.pdf Assortative mixing in networks]
* [http://www.cis.upenn.edu/~mkearns/teaching/NetworkedLife/prefatt.pdf Mean field theory to study scale-free networks]
* [http://www.graphanalysis.org/SIAM-PP08/Leskovic.pdf Kroneker Graphs]
* [http://www.lem.sssup.it/WPLem/files/2011-07.pdf Exact maximum-likelihood method to detect patterns in real networks]
* [http://www-users.york.ac.uk/~lsdc1/SysBiol/kitano.robustness.naturegenetics.2004.pdf Biological robustness]
* [http://arxiv.org/ftp/cond-mat/papers/0202/0202410.pdf Attack vulnerability of complex networks]
* [http://jmvidal.cse.sc.edu/papers/nair11a.pdf Supply Network Topology and Robustness against Disruptions – an investigation using multi agent model]

* [http://arxiv.org/abs/cond-mat/0007235 Random graphs with arbitrary degree distributions and their applications]
* [http://www.pnas.org/content/104/1/36 Resolution limit in community detection] - about a typical modularity measure and its limitations

* Add a relevant paper...

== Learning Python ==
* [http://code.google.com/edu/languages/google-python-class/ Google's Python Class]
* [http://networkx.lanl.gov/tutorial/tutorial.html Networkx Python lybrary]
* [http://networkx.lanl.gov/reference/algorithms.html Networkx graph algorithms]
* [http://networkx.lanl.gov/reference/drawing.html Networkx drawing]

== Participants ==
# [[Oleksandr Ivanov]] - krystoferivanov@gmail.com
# [[Ian Wood]] - ibwood@indiana.edu
# [[Xin Lu]] - xin.lu@ki.se
# [[Duenas-Esterling Marco-Antonio]] - maduenase@gmail.com
# [[Katrien Beuls]] - katrien@ai.vub.ac.be
# [[Cameron Ray Smith]] - [http://www.google.com/recaptcha/mailhide/d?k=01_G1kMsuOrJhiwcXbYs5uYQ==&c=4iKaQQLKYQ-uUaepLzz3_1LdZfwZMM24y5sG4GTjP-4= c...@gmail.com]
# [[Abby Horn]] - abbyhorn@mit.edu


== Source Control ==
I've set up a github repository for any python source we write [https://github.com/ibwood/CSSS-Network-Robustness-Project here].
To figure out how to use Git look [http://git-scm.com/book here]. Chapters 1,2,3, and 5 are particularly relevant, but I can run through the basics with anyone. It's useful to have a source control for both project coordination and backup, and git is very simple once you get the hang of it.

There is a shared folder on skype, please either sign your email in the participant list or drop a email to [[Xin Lu]] to access the generated network data. Dropbox link [https://www.dropbox.com/sh/y6e5ukftde4yt7x/i4ZZ03Yr_5]

== BA algorithm in Python ==
* [http://networkx.lanl.gov/_modules/networkx/generators/random_graphs.html#barabasi_albert_graph Networkx source]

== BA network + modularity ==
* [http://networkx.lanl.gov/_modules/networkx/generators/random_graphs.html#powerlaw_cluster_graph Networkx source]

Complex Systems Summer School 2012-After Hours

2012-06-10T03:41:58Z

AHorn: /* Prometheus */

{{Complex Systems Summer School 2012}}

Use this space to organize your own after hours activities.

==Prometheus==
While I have a rental car that seats up to 5, I've been thinking of going to see Prometheus in theaters. It shows tonight the 9th at 10:40 so we need to meet at the visitor's circle at 10:25, if anyone's interested. more than 5 people will require another car or taxis.

1. Ian

2. John

3. Fabio

4. Gareth

==Saturday Football==

Who is up for a quick match tomorrow at 8am before the Bandelier trip? Let's make it a relaxed, just-for-fun match. Sign up below:

- [[Miguel Lurgi|Miguel]]

==Bandelier Field Trip==

Bandelier Field Trip
Trip to Bandelier National Monument on Sat. June 9.
We might string a visit to the Valles Caldera and Bradbury Science Museum/Los Alamos in as well. If another group would like to stay around Bandelier, we can split up.

Head over to the [[Bandelier Trip 2012 | Bandelier Trip]] Page to sign up!

==Mafia==

[[JP]] is a huge fan of Mafia/Werewolf. Let's play a game sometime in the lower commons.

Let's meet Saturday evening at 8:00 in the lower commons for our first game.

- [[Ryan_James|Ryan]] is down for this.

- Jasmeen is also a big fan of Mafia.

- Ian has never played, but is interested

- Vikram is interested in learning the game.

- Tom F. would like to join and can also teach "The Resistance" a very similar game

==FOOTBALL!==

Anyone up for a friendly game of soccer? We can check out equipment from the gym.

[Team: Continuous!] 
1. [[Piotr Milanowski|Piotr]] 
2. [[Marco Duenas|Marco]] 
3.[[Oleksandr Ivanov|Alex]] 
4. 
5. 
[Team: Discrete!] 
1. [[Fabio Cresto Aleina|Fabio]] 
2. [[Matteo Chinazzi|Matteo]] 
3.[[JP]] 
4. 
5.

Complex Systems Summer School 2012-After Hours

2012-06-10T03:32:30Z

AHorn: /* Prometheus */

{{Complex Systems Summer School 2012}}

Use this space to organize your own after hours activities.

==Prometheus==
While I have a rental car that seats up to 5, I've been thinking of going to see Prometheus in theaters. It shows tonight the 9th at 10:40 so we need to meet at the visitor's circle at 10:25, if anyone's interested. more than 5 people will require another car or squishing

1. Ian

2. John

3. Fabio

4. Abby

==Saturday Football==

Who is up for a quick match tomorrow at 8am before the Bandelier trip? Let's make it a relaxed, just-for-fun match. Sign up below:

- [[Miguel Lurgi|Miguel]]

==Bandelier Field Trip==

Bandelier Field Trip
Trip to Bandelier National Monument on Sat. June 9.
We might string a visit to the Valles Caldera and Bradbury Science Museum/Los Alamos in as well. If another group would like to stay around Bandelier, we can split up.

Head over to the [[Bandelier Trip 2012 | Bandelier Trip]] Page to sign up!

==Mafia==

[[JP]] is a huge fan of Mafia/Werewolf. Let's play a game sometime in the lower commons.

Let's meet Saturday evening at 8:00 in the lower commons for our first game.

- [[Ryan_James|Ryan]] is down for this.

- Jasmeen is also a big fan of Mafia.

- Ian has never played, but is interested

- Vikram is interested in learning the game.

- Tom F. would like to join and can also teach "The Resistance" a very similar game

==FOOTBALL!==

Anyone up for a friendly game of soccer? We can check out equipment from the gym.

[Team: Continuous!] 
1. [[Piotr Milanowski|Piotr]] 
2. [[Marco Duenas|Marco]] 
3.[[Oleksandr Ivanov|Alex]] 
4. 
5. 
[Team: Discrete!] 
1. [[Fabio Cresto Aleina|Fabio]] 
2. [[Matteo Chinazzi|Matteo]] 
3.[[JP]] 
4. 
5.

Bandelier Trip 2012

2012-06-07T02:54:43Z

AHorn: /* STILL NEEDS A SEAT! */

{{Complex Systems Summer School 2012}}

Please sign up here so we know who's going. 
Also: If you have a car, please let us know. The more cars, the more people. 

We'll meet Saturday at 10:00am in the parking circle.

Please remember to bring a hat, sunscreen, water, hiking shoes, and anything else you'll need for a day out in the field.

==Cars:==

===Tom's Sedan: 4 seats===
1. [[Nicholas Allgaier]] 

2. Vikram Vijayaraghavan 

3. Katrien Beuls 

4. Riccardo Fusaroli 

===John Paul's Camry: 4 (maybe 5) seats===

1. [[John Paul]] 

2. [[Matteo Chinazzi]] 

3. [[Chloe Lewis]] 

4. [[Xue Feng]] 

5. [[Joanne Rodrigues]] 

===Juniper's Car: 4 seats===

1. Jasmeen Kanwal

2. Sarah Tweedt

3. Mark Longo

4. Hide Inamine

===[http://tuvalu.santafe.edu/events/workshops/index.php/Christa_Brelsford Christa]'s Car: 4 (maybe 5) seats===

1. Christa

2. Nicolas Goudemand

3. Marco

4. [http://tuvalu.santafe.edu/events/workshops/index.php/Xin_Lu Xin]

5(middle seat in a 2 door civic). [[Miguel Lurgi]]

===STILL NEEDS A SEAT!===
1. Priya Subramanian

2. [[Piotr Milanowski | Piotr]]

3. Georg M Goerg

4. Oleksandr Ivanov

5. Ben Althouse

6. Georg Weber

7. Oscar Patterson

8. David Pugh

9. Abby Horn

Complex Systems Summer School 2012-Projects & Working Groups

2012-06-06T20:53:29Z

AHorn: /* Relevant literature */

{{Complex Systems Summer School 2012}}

==Project proposals==

=== Nonequilibrium game theory ===
My hope is to adapt some SFI-based models, by people like Crutchfield and Farmer, so that they will quantitatively or qualitatively reproduce features of real human data. Of course, that is very specific, and I'm up for all kinds of ideas in the areas of game learning, game dynamics, small group collective behavior, cognitive science, nonlinear time series, non-eq time series, etc., etc.

Meet me, Seth Frey, at dinner on Thursday and Friday. Also, here's a [http://posterhall.org/igert2012/posters/218 fun 3-minute video] of the effect I'm personally the most interested in, with a special appearance from The Princess Bride.

=== Enzyme kinetics – Do enzymes just accelerate equilibrium or play an active role in chemical reactions? ===
Enzyme networks (e.g. glycolysis) and catalysts in complex mixtures (e.g. Belusov-Zhabotinski reaction) can profoundly influence the outcome of a chemical reaction system. What about a single enzyme? Biochemistry textbooks uniformly say that an enzyme accelerates a reaction without altering its outcome. Yet, the set of differential equations that generically describes enzyme catalysis has remarkable resemblance to the Roessler equations (a textbook example of a non-linear, complex system). With a fixed substrate input or a steady substrate flow, a single enzyme probably cannot affect the reaction outcome. However, sinusoidal or pulsating substrate input, substrate activation or product inhibition, coupling of two enzymes could turn the reaction pattern non-linear. For this project, the sets of equations to study are quite well established – they need to be analyzed. In contrast to some of the more ambitious ideas circulated, this task is exhaustively doable in less than four weeks.

I am Georg Weber. If you are interested in studying this problem, please find me on Tuesday over lunch or dinner (or talk to me at any other unstructured time).
=== Traffic pattern analysis - Can we estimate car velocity by only observing car counts? ===
==== Problem statement ====
Imagine you have a monitored highway section with a start and end point. At both points you count the number of cars that pass by. The question I'd like to answer / simulate / estimate is: can we make some inference about the velocity of cars although we only have their counts? This would be very useful from an engineering / economic perspective because it's much easier / cheaper to count cars instead of actually tracking them from A to B.
==== Ideas on how to approach this ====
I have some intuition about how to go about this, but these are purely statistical (think of it as birth and death process; or as particles in a system that have a certain lifetime - cars in the highway section are like particles in a system, and their velocity is just inverse proportional to their lifetime in this highway section). I would like to see if using explicit physical modeling of motion and agent-based modeling of traffic flow could shed more light on this problem.

'''Update 06/05/12:''' Just today we saw ''Takens theorem'' about how we can infer a systems structure from only observing a subset of variables. Well, it seems like that's exactly what this project is about.

If you are interested to see more about this check out the [[Georg_M_Goerg#SFI_Project:_Traffic_pattern_analysis_-_Can_we_estimate_car_velocity_by_only_observing_car_counts.3F_.3D|SFI Project]] subsection on [[Georg_M_Goerg|Georg M. Goerg]] or email me to my_3_initials_in_lowercase@stat.cmu.edu. Let's say we meet on Wednesday for lunch (or just ask me any other time you see me around).

=== Cultural Evolution - General Meet-up ===
Attention anyone who is interested in cultural evolution or applying your models/methodologies to this fabulous topic!

Let's meet at 4:15 (June 5th) in the cafe during the first "Time to work on Projects" slot. A bunch of us coalesced there tonight and figured we should all properly meet up and then bud off into different projects. Please post your potential buds below:

=== Cultural Evolution - things that look like drift but aren't ===
Lots of cultural evolution looks like drift (Bently et al 2004 'Random drift and culture change"). But what social transmission or cognitive learning mechanisms are isomorphic to random sampling with replacement from cultural inputs? In biological evolution, drift serves as a null model of sorts - one that should be ruled out before you can claim that anything more interesting is happening. However, it's not clear what the "uninteresting" type of change is for things that replicate by passing through human cognition and human social systems - like culture does. Is there even a reasonable equivalent of drift in cultural transmission? How should we go about conceptualizing and modeling the evolutionary forces at play in culture?

One candidate for a drifty-lookin' human behavior is probability matching: when people reproduce similar distributions of variation to that which they've learned from. And probability matching is rampant in human behavior (from language learning, to decision making, and even at the neural level). But I think this is a clearly different process than drift, however it still may qualify under Bentley's vague criteria - we can test that out. And there have got to be more drift-esque processes, anyone have any ideas?

If you're interested in these issues or modeling evolution (of any type of system), please give me a shout!

Vanessa

vanferdi [at] gmail.com

==="Small Steps and Big Ideas" Group===

[http://tuvalu.santafe.edu/events/workshops/index.php/Christa_Brelsford Christa] [http://tuvalu.santafe.edu/events/workshops/index.php/Daniel_Wu Dan] [http://tuvalu.santafe.edu/events/workshops/index.php/Xin_Lu Xin] and Tom spent a while talking after dinner about a bunch of big ideas. Some things we thought about were *big data type network problems, *integrating qualitative social information with models of physical systems, *using games to understand cooperation and decision making.

We'll meet at dinner at 5:30 today (Tuesday, June 5th) in the cafeteria.

=== 107 Proteins in 10-15 cubic meters ===
Cells rely on proteins to perform vital metabolic and signaling functions; however, it is unclear how proteins are successfully directed to their necessary cellular location(s) in a densely-packed macromolecular environment within the cytoplasm and on the cellular membrane in a short timescale (see for example [http://www.pnas.org/content/108/16/6438.full Weigel et al., PNAS 2011]). Using the cell as a manipulatable model of complexity, one could begin to define the parameters and questions, as they pertain to prokaryotic and eukaryotic cells. If interested, please drop me a line: Sepehr Ehsani; sepehr.ehsani[at]utoronto.ca.

=== Innovation and Technological Progress ===

I noticed that a number of people mentioned that they were interested in some way in relation to innovation. I was wondering if anyone was interested in a project looking at how particular technologies progress over time and whether charting the form of successful (and/or unsuccessful) previous technologies such as the transistor, fission reactor, mobile phone, etc. in terms of either price, efficiency, or some other variable may be useful in predicting whether a current technology such as solar PV, fuel cell, or something else is following a similar trajectory. Other possible ideas might be to look at using patent, publication, or collaboration network data to reveal certain features of innovation that are not captured by other statistics, particularly for technologies that have yet to reach the market. SFI Professor Doyne Farmer has looked at some of this already in 'The Role of Design Complexity in Technology Improvement', see link: http://adsabs.harvard.edu/abs/2009arXiv0907.0036M

This could be a jumping off point for some ideas on data, methods, models etc. Just throwing the idea out there and it's welcome to completely change but if you're interested, message me (Gareth Haslam) haslam@ias.unu.edu or find me in class.

=== Space, Stochasticity, Stability; Speciation? ===

[http://tuvalu.santafe.edu/events/workshops/index.php/Xue_Feng Xue], [http://tuvalu.santafe.edu/events/workshops/index.php/Chloe_Lewis Chloe] and [http://tuvalu.santafe.edu/events/workshops/index.php/Xiaoli_Dong Xiaoli]are all working in ecosystems that experience_ a lot of unpredictability in a limiting ecosystem variables (water and/or nutrients); we see patchiness in space and time in how organisms are arranged; and we have some ideas about how the stochasticity may cause the spatial arrangements. [http://tuvalu.santafe.edu/events/workshops/index.php/Si_Tang Si] is working on the stability and robustness of ecosystems.

With enough time, this is likely to involve speciation either to express different strategies, or as a result of spatial separation.

The [[Spatial-Stochastic]] group is writing up their ideas to share here and look for overlap and coupling.

=== Plasticity in Neural Networks ===
I've done some modeling which shows that the amount of genetic variation that accumulates at any particular metabolic gene (enzyme) in a population at any given time is a function of the network topology in which the gene is embedded, as well as the distance of the network output from an optimum. So, for instance, in a linear metabolic network, enzymes at the beginning of a pathway will tend to be more constrained (show less variation in the population) than at the end of the pathway. This makes sense given that any changes in those first genes would ripple through the system and have a greater relative effect than mutations in later genes. However, this is only true when a population is already close to an optimum. When far from an optimum, we see the exact opposite trend with more variation in the front of the pathway. This also makes sense - when far from a goal, taking bigger steps gives individuals a better chance of achieving higher fitness. The system as a whole then uses the different relative step sizes according to pathway position to "fine tune" its output.
I think these findings are quite general - at least the model we used was simple enough that it could apply to many different types of directional developmental processes. We can conceptualize these "genes" more generally as sequential steps in a developmental process with some arbitrary goal. These could be steps in a factory assembly line, major product revisions versus minor releases, or (and this is my favorite), neurons learning about their environment. I'm curious what would happen if we took a similar approach to model neural networks. Genetic variation is the raw material for evolution while neural plasticity is the raw material for learning. The question we would be trying to answer is where, within a neural network, would we expect the most plasticity given a particular network topology and distance form a learning goal.
Please contact me (Mark Longo) if this sounds interesting. I'll be available during unstructured time, or you can email mlongo@stanford.edu.
[http://tuvalu.santafe.edu/events/workshops/index.php/Mark_D._Longo]

=== Robustness of complex networks ===
[[File:Zoo.png|thumb|300px|Fig. 1. Zoo of complex networks (an example). Taken from Sol´e and Valverde, 2001.]]
==== Problem statement ====
Complex networks have various properties which can be measured in real networks (WWW, social networks, biological networks), e.g. degree distribution, modularity, hierarchy, assortativity etc. Robustness of complex networks is a big question, however only some progress have been done in this direction. For example, it was shown that the scale-free networks are much more topologically robust to random attacks than random networks. Many people claim that various characteristics of complex networks will influence the robustness interdependently. The question I am interested in is how?

==== Approach ====
The idea is to generate continuous topology space of various complex networks (networks with different modularity, degree distribution, hierarchy etc) and use it to measure their robustness (see Fig. 1). There are many approaches to measure the robustness of complex networks. For example we can remove edges of vertices of a complex network graph and look at the size of a giant cluster. We can discuss other possibilities.

If you are interested you can contact me directly or via my E-mail: krystoferivanov@gmail.com or via my [[Oleksandr Ivanov|discussion page in CSSS 2012 wiki]].

==== Relevant literature ====
* [http://www.barabasilab.com/pubs/CCNR-ALB_Publications/199910-15_Science-Emergence/199910-15_Science-Emergence.pdf BA Scale-free network]
* [http://people.maths.ox.ac.uk/maini/PKM%20publications/195.pdf How to generate Scale-free modular network using preferential attachment]
* [http://www.barabasilab.com/pubs/CCNR-ALB_Publications/200007-27_Nature-ErrorAttack/200007-27_Nature-ErrorAttack.pdf Error and attack tollerance of complex networks]
* [http://www.cis.upenn.edu/~mkearns/teaching/NetworkedLife/hierarchical.pdf Hierarchical organization in complex networks]
* [http://arxiv.org/pdf/cond-mat/0402009v1.pdf Scale-free networks with tunable degree distribution exponents]
* [http://arxiv.org/pdf/cond-mat/0110452v1.pdf Scale free networks with tunable clustering]
* [http://vw.indiana.edu/netsci06/conference/Ng_Structural.pdf Structural Robustness of Complex networks]
* [http://arxiv.org/pdf/cond-mat/0205405.pdf Assortative mixing in networks]
* [http://www.cis.upenn.edu/~mkearns/teaching/NetworkedLife/prefatt.pdf Mean field theory to study scale-free networks]
* [http://www.graphanalysis.org/SIAM-PP08/Leskovic.pdf Kroneker Graphs]
* [http://www.lem.sssup.it/WPLem/files/2011-07.pdf Exact maximum-likelihood method to detect patterns in real networks]
* [http://www-users.york.ac.uk/~lsdc1/SysBiol/kitano.robustness.naturegenetics.2004.pdf Biological robustness]
* [http://arxiv.org/ftp/cond-mat/papers/0202/0202410.pdf Attack vulnerability of complex networks]
* [http://jmvidal.cse.sc.edu/papers/nair11a.pdf Supply Network Topology and Robustness against Disruptions – an investigation using multi agent model]

* Add a relevant paper...

=== Systemic Risk in Financial Networks and/or an ABM of money/liquidity===

'''Systemic Risk in Financial Networks:''' Hypothesis: the motive to diversify risk at the level of the individual agent (i.e., for an agent to increase its connectivity) will increase systemic risk (by systemic risk I mean vulnerability of the system to widespread collapse). Point of departure is the [http://en.wikipedia.org/wiki/Forest-fire_model Forest Fire] model from statistical physics.

Key difference(s) between the physics version of the Forest Fire model, and the "economics" version of the Forest Fire model I have in mind are:
* Tree growth probability (which determines network structure) must be endogenous. Agents must be able to choose which other agents to link with.
* Probability of lightning strikes (i.e., defaults on specific loans) must also be endogenous.

I think that financial networks might exhibit self-organizing criticality in the sense that diversification will reduce the probability of lightning strikes (i.e., defaults), however over time systemic risk builds up as a result of the diversification which means that eventually a small number of lightning strikes might be enough to bring the entire system down.

'''ABM of the emergence of Money:'''
Basically, I would be interested in building an ABM of the emergence of money based around the following economic models of money developed by Nobu Kiyotaki and John Moore:
* [[File:Kiyotaki_and_Moore_(2001).pdf | Evil is the Root of all Money]]
* [[File:Financial-Deepening.pdf | Financial Deepening]]

These models take a broad view of money: "money" is any asset which is widely accepted as a medium of exchange. In these models agents manage projects which require capital investment now in order to generate a return at some point in the future and agents must trade financial promises (think debt contracts) in order to obtain the needed investment. Two key parameters of is these models (which are assumed COMMON to all agents in the above models in order to maintain analytical tractibility) are 0 < theta < 1 and 0 < phi < 1. Theta is the fraction of the future return from the project that an agent can promise to repay in the future in exchange for investment now. Phi is the fraction of the face value of a debt contract (which by construction is a contract between two agents) that can be re-sold to a third agent.

Hypothesis: In an ABM where agents differ in terms of both theta and phi, the promises of only a small number of agents will be widely traded (i.e., will serve as money).

If anyone might be interested in working on these projects, send me and email: drobert.pugh at gmail dot com

=== Price-time dynamics of contracts traded on prediction markets===
Prediction markets have been shown to outperform traditional methods of polls and opinion surveys in forecasting future events. I am interested in exploring the price-time dynamics of contracts traded on prediction markets to better understand how they are able to aggregate individual opinion to establish collective insight.

Several questions that I’m curious to probe further:
* How do ‘information shocks’ generated by news sources influence price-time trajectories?
* Can features of the underlying dynamics be characterized using a simple model?
* What is the minimum number of traders required for an accurate prediction?
On a separate note, I invite you to share your opinion regards whether “China will win the most medals at the 2012 London Olympics”, by logging into the following [https://csss12.inklingmarkets.com/user/login site] (please send me your email address and I will send you the login details).

If you haven't used a prediction market before don't worry -just follow the instructions provided in the site to 'buy' and 'sell' contracts according to your expectation.

If you are interested in the discussing any of the above questions or have other ideas related to prediction markets please get in touch with me at: sanith at mitre dot org

=== Internal models: what do they do and how are they built?===
In the past decade(s) Bayesian statistics has come to dominate empirical science. Consequently, the significance of prior beliefs for guiding inference has become widely accepted. But how do we map the concept of prior beliefs onto natural systems? I argue that the composition of organisms realize internal models of their environment. These internal models manifest as structured behavior, which we scientists describe as reflecting prior beliefs or bias. In humans you have reflexes at one extreme and the influence of memories upon behavior at the other. It is an open question how these internal models are instantiated in biological systems. Are they structural motifs in neural networks? Protein networks within cells? Concepts such as memory, storage, and recall provide relevant bridges between the statistical formulation of these ideas and the physics of computation, but these are jumping off points at best.

My suspicion is that part of the challenge is we don’t have a clear understanding of what benefits internals models impart to organisms beyond some general statement about resolving uncertainty. This is compounded by the fact that we probably wouldn’t recognize an internal model if we saw one. This is why I find work over the past decade upon self-localizing and mapping (SLAM) systems to be so interesting. To my knowledge, these are the first man-made systems designed with the objective of imparting complex internal models to artificial systems. The Mars rover is a SLAM system. The driverless car depends critically upon a SLAM system. The successes, and failures, of these systems have exposed the complexity of functionalities we use so naturally that they evade our notice. These include differentiating between static and dynamic elements of our environment as well as ascribing our sensations to external or internal causes. In the least, the design of these systems offer first order models for what an internal model of non-trivial complexity might look like.

I’m interested in exploring the role of internal models as well as how they are embedded in natural systems. I welcome you to join to me to discuss these ideas in the Cafeteria after 3 on Wednesday and after 4 on Thursday. Feel free to email me at: jlong29@gmail.com (John Long)

=== Rain-Cimate-Agriculture Interactions ===

We are trying to think about the influence of different precipitation/climate regimes on farming strategies and crop prices. It is still a very vague idea, and we're meeting at 4:15 in front of the cafeteria to brainstorm a bit (possibly outside). If you're interested in it, you're very welcome to join us! fabio.cresto-aleina@zmaw.de and fgreb@uni-goettingen.de

File:Mepic-1-.png

2012-06-04T06:48:04Z

AHorn:

Abigail Horn

2012-06-04T06:47:20Z

AHorn:

Hi CSSS 2012!

I am informally known as Abby.

My PhD research, which I'm just beginning in MIT's Engineering System Division, involves identifying the source of spreading in foodborne disease outbreaks. I want to explore the feasibility and practicality of creating aggregated distribution networks for specific commodities and using basic connectivity analysis to narrow down the source identification problem. I'm just beginning to learn how complex and uncertain outbreak tracebacks can be, and would love to hear the thoughts of those of you who have some experience in outbreaks or tracebacks of any kind! I'm also looking for structures to borrow from, so any ideas on what (well-documented) networks might resemble food distribution networks are very much welcomed!

More generally, I am interested in understanding food distribution networks: their general properties (and resilience to disease spreading as they become larger), and behavior such as scaling laws and diffusion patterns. What parameters most influence these behaviors?

Even more generally, I'm interested in exploring the problem of inferring the source of an epidemic in populations, given the limitation of possible observations, and any kind of source of spreading problem in a network – epidemic, traffic, rumors…

My undergrad was at the College of Creative Studies at UC Santa Barbara, where I majored in physics and the farmer's market. I have some experience in machine learning (classification of prognosis of sepsis patients) and assessment of low-probability, high-consequence events befalling water distribution networks; also in teaching engineering systems to undergraduates! And I’m getting into the power of probability and am eager to learn more about stochastic processes and stochastic networks.

I am so eager to hike run and explore this area to the maximum in the legacy of Robert Oppenheimer (whose biography, American Prometheus, is both excellent and highly appropriate)!!

Abigail Horn

2012-06-04T06:44:22Z

AHorn: Created page with 'Hi CSSS 2012! I am informally known as Abby. [[File:mepic[1].png]] My PhD research, which I'm just beginning in MIT's Engineering System Division, involves identifying the sou…'

Hi CSSS 2012!

I am informally known as Abby.

[[File:mepic[1].png]]

My PhD research, which I'm just beginning in MIT's Engineering System Division, involves identifying the source of spreading in foodborne disease outbreaks. I want to explore the feasibility and practicality of creating aggregated distribution networks for specific commodities and using basic connectivity analysis to narrow down the source identification problem. I'm just beginning to learn how complex and uncertain outbreak tracebacks can be, and would love to hear the thoughts of those of you who have some experience in outbreaks or tracebacks of any kind! I'm also looking for structures to borrow from, so any ideas on what (well-documented) networks might resemble food distribution networks are very much welcomed!

More generally, I am interested in understanding food distribution networks: their general properties (and resilience to disease spreading as they become larger), and behavior such as scaling laws and diffusion patterns. What parameters most influence these behaviors?

Even more generally, I'm interested in exploring the problem of inferring the source of an epidemic in populations, given the limitation of possible observations, and any kind of source of spreading problem in a network – epidemic, traffic, rumors…

My undergrad was at the College of Creative Studies at UC Santa Barbara, where I majored in physics and perhaps also the farmer's market. I have some experience in machine learning (classification of prognosis of sepsis patients) and assessment of low-probability, high-consequence events befalling water distribution networks; also in teaching engineering systems to undergraduates! And I’m getting into the power of probability and am eager to learn more about stochastic processes and stochastic networks.

Last but not least, I am very eager to hike run and explore this area to the maximum in the legacy of Robert Oppenheimer (whose biography, American Prometheus, is both excellent and highly appropriate!)

Alfred Hubler's Nonlinear Dynamics Lab 2012

2012-06-03T23:48:47Z

AHorn: /* Monday, June 11, 6:00pm */

{{Complex Systems Summer School 2012}}

==Thursday, June 7, 6:00pm==

1. Sarah Tweedt 
2. Georg F. Weber 
3. Georg M. Goerg 
4. Cameron Smith 
5. Mikkel Vestergaard 
6. Friederike Greb 
7. Fabio Cresto Aleina 
8. Benji zusman 
9. Elena del Val 
10.Riccardo Fusaroli 
11. Nick Allgaier 
12.John Long 
13. Sepehr Ehsani 
14. David Pugh 
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==Friday, June 8 7:00am==
PLEASE NOTE THAT THIS IS AN EARLY MORNING CLASS! 
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==Monday, June 11, 6:00pm==
1. Hidetoshi Inamine 
2. Dan Wu 
3. Xiaoli Dong 
4. Si Tang 
5. Abby Horn 
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==Tuesday, June 12, 6:00pm==
1. Marco Duenas

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