Complex Systems Summer School 2014-Projects & Working Groups

Complex Systems Summer School 2014 Home Surveys/Evaluations Logistics Payment Instructions Faculty Lecture Slides Panel Questions Panel Responses Participants 1-Minute Summaries Schedule Background Readings Software Projects & Working Groups Project Group Meeting Schedule Sign Up Sheet for Meetings with Miguel and Josh Tutorials Blog Project Presentations Final Papers After Hours Restaurant Guide Resource Guide Photos TShirts

MITRE Data Sets

To access the data please contact Juniper she has it on a hard drive. Here is a PDF that explains the datasets and gives some sample challenge questions. MITRE DATA PDF If you have any specific questions about the data you can contact Matt Koehler at mkoehler@mitre.org

Death in physical, biological and social systems

Firms, nation states, human beings and stars all die. Do the causes of "death" in physical, biological and social systems have something in common? If yes, what is it?

Interested

Vipin

Fractal-like structures in economic data

In the 1960-70s Mandelbrot showed that some economic time series have fractal-like structures, i.e. they look the same at many time scales. The existence of these structures has been debated since. Do economic time series like S&P 500 index have fractal-like structures? If yes, how fractal-like are they?

Interested

Vipin

Microbial Community Data Sets

The Earth Microbiome Project EMP is a massively multidisciplinary effort to analyze microbial communities across the globe. The general premise is to characterize the Earth by environmental parameter space into different biomes and then explore these using samples currently available from researchers across the globe. All data sets are processed in the same way (DNA extraction, PCR primers, sequencing, bioinformatics), making them inter-comparable. You can explore these data sets (including some time series, and a bunch of spatial samplings) at the following link EMP Data (no need to create a login ID, just scroll down to 'Download Public Data'). If you have questions, please contact Sean Gibbons (sgibbons at uchicago dot edu).

Does Larger Memory Capacity Brings about Evolutionary Advantage?

Evolutionary game theory modeling. Agents/players on lattice or networks. A player with n-step memory has responses to all 4^n past game outcomes. Intuitively, a player with longer memory can have more sophisticated strategy, which might be used to exploit player with smaller memory capacity. Yet according to the Prisoner's Dilemma tournament organized by Axelrod, Tit-for-Tat, which can be modeled using only one-step memory, fares better than a number of sophisticated strategies invented by experts in the field of game theory. From the game theory perspective, does smaller memory capacity actually have evolutionary benefits?

North American Breeding Birds Survey and tropical trees

This dataset contains ~4500 sites where populations of birds (~600 species overall, ~60 species on average in every site) were sampled over the past 44 years. This gives numerous time series of both population sizes and the overall number of species. Some problems with this dataset include large observational errors. A dataset of tropical trees with the exact diameter, identity (from among 300 species) and location of ~250000 trees over 6 censuses is also available. Please contact Michael Kalyuzhny for these.

Santa Fe tournament of time series analysis!

Do fluctuations in timeseries arise from nonlinear dynamics or from stochasticity? Specifically, there are several examples of ecological time series where chaos/complex periodicity were found (and published in Science and other leading journals). But usually such analyses didn't examine alternative models of stochastic dynamics. I propose making some meta-analysis and trying to compare the predictive power of both kinds of models. This can also be done in other fields were such timeseries are available. If you want to talk about this - contact Michael Kalyuzhny

Emergence and Persistence of Norms on Networks

How does the structure of social networks affect the emergence and persistence of norms? Why are some norms (like fashion styles) less persistent than others (like religious beliefs)? Is this because different kinds of norms live on different social networks (with same individual participating in different networks)? If yes, how do these social networks interact?

And finally, what do the answers to the above questions tell us about policy interventions? Can certain critical properties of network structures be exploited to change norms, like going to the moon without much fuel? If two networks interact, say religious belief and fashion styles, can interventions in one be used to bring about changes in another?

Interested

Vipin

Network Tolerance of Failure

How might a network endure non-catastrophic failure without isolating the failing components? Most network failure models consider resilience against failure as a result of isolating failing components. In contrast, is it possible for the network to be robust through "tolerance" of failure? Perhaps, for example, a symbiotic relationship sustains a weakened node until it has recovered its prior performance. Or perhaps a transmitting network retains a connection to an offline node to reduce an anticipated memory load of re-establishing the connection when it comes back online. What are some of the ways in which networks are able to maintain connection to a failing node without failing themselves in the process - how is the cascade halted without isolation? This is meant to be a broad question to generate more specific ideas. Importantly, this question refers to "tolerance of" failure in contrast to "resilience against" failure.
Contact: Jessica Santana jsant@stanford.edu