Complex Systems Summer School 2014-Projects & Working Groups
From Santa Fe Institute Events Wiki
| Complex Systems Summer School 2014 |
Bitcoin
Bitcoin is an online peer-to-peer currency which has gained popularity in recent years. With increased general interest and now more and more companies accepting transactions in Bitcoin, so to has its value and is currently priced at $633 for 1 Bitcoin!
So what is Bitcoin?
The idea behind Bitcoin was to remove the need for a centralised banking system. The way this works is to have all transactions made public and then have the Bitcoin community validate transactions by donating computational power (and rewarded in Bitcoins). For further details see this blog:
http://www.michaelnielsen.org/ddi/how-the-bitcoin-protocol-actually-works/
So why is it interesting?
Usually companies and individuals keep all of their financial records private, but ALL transaction in Bitcoin are publicly available, so this provides a unique opportunity to study financial transactions. While the transactions are public, the owners of Bitcoin remain (relatively) anonymous, and so this has led to associations with criminal activities (e.g. on the silk road) from illegal drugs to hired hit-men. In addition to illegal activities using the currency, there have also been a number of illegal activities against the currency, such as high valued heists of the order of $100 million.
Oh, and of course its a big temporally evolving network.
If you're interested in working on this then add your name below. If there is interest, then we can have a "Bitcoin, beers and blackboard" session to throw some ideas around.
Interested:
Leto
Shai
Flavia
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
Blaz
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? Please contact Degang Wu (dwuab@ust.hk).
Interested:
Blaz
Brian
Flavia
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
Interested:
Michael Kalyuzhny
Degang Wu
The Multiplex 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
Sarah L
Alberto
Francesca
Nhat (nhattdnguyen@gmail.com)
Sanja
Massimo
Leto
Alireza (alireza.goudarzi at gmail.com)
Claire (lagesse.claire at gmail.com)
Cecilia
Sean Hayes (shaye004@ucr.edu)
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
Interested:
James Holdener
Junjian Qi
Ells Campbell
Leto
Alireza (alireza.goudarzi at gmail.com)
Claire (lagesse.claire at gmail.com)
Sean Hayes(shaye004@ucr.edu)
Influence of different types of parasites and pathogens in networks on dynamics and stability of food webs
In nature there is a number of infectious agents which have different evolutionary approaches in way how they influence their hosts. We want to built artificial ecological network and to compare how these evolutionary solutions affect stability of food webs.
Contact: sanjakojasanja@gmail.com
Interested:
Stojan
Nhat (nhattdnguyen@gmail.com)
Sanja
Cecilia: Are we going to discuss today at 9?
No probably, but tomorrow, today is a free day! Relax!:D
Growth of Cities
Do foraging animals and growing cities utilize resources in the same way? We're interested in building an agent-based model which generates a road network on a map of varying resources by following a set of simple, probabilistic rules. How do the properties of this network evolve through time? How much of city growth can be explained by resource constraints? Do simple rules of growth parallel simple rules of animal foraging behavior? This project will explore agent-based modeling, but will also present opportunities to examine the limits of modeling. Contacts: Diana LaScala-Gruenewald (dianalg11 at gmail.com) and Claire Lagesse (lagesse.claire at gmail.com).
Interested:
Morgan Edwards
Rohan Mehta
Alberto Antonioni
Ernest Liu
Michael Kalyuzhny
Hiroshi Ashikaga (hashika1@jhmi.edu)
Towards a Unified Theory of Biodiversity
The idea is to build on the Unified Neutral Theory of Biodiversity and create a realistic unified theory that incorporates important power-scaling laws, energetic constraints, and stochasticity that have been previously neglected. Still checking with external collaborators if they are not working on the idea.
Interested:
Diego Barneche Rosado
Cornelia Metzig
Michael Kalyuzhny
Coupling of different types of networks
We want to develop a concept of how to work with networks of qualitatively different types of relationships or interactions that can influence each other (eg. natural and social). Sign up and come to brainstorm with us :) Contact: sanjakojasanja@gmail.com
For example, people's beliefs about the health benefits/risks of vaccination can be influenced by their social network, and may be studied using belief propagation models. Simultaneously, diseases may spread through a population, which can be studied using diffusion or other epidemiological models. Furthermore, people's beliefs about vaccination may affect their probability of getting infected by a disease, and in turn, getting infected may cause them to re-evaluate their beliefs.
Another example could involve an ecological network expressing predation and competition among species, and environmental factors affecting the natural resources in the system.
Interested:
Sanja
Fahad
Brian
Nhat (nhattdnguyen@gmail.com)
Consciousness as an emergent state of matter – what do you think?
You’re conscious right now, reading this. How does subjective experience emerge out of the bundles of particles that we all are?
Scholars of many fields have been deconstructing the mind/body dualism for a while, but consciousness remains a big, hard question. I’m no expert and by proposing this as a topic I’m not expecting that any of us will solve it, but I would be very interested in exchanging on the issue with the smart individuals that you are, grounded in so many backgrounds and unafraid of complex problems.
So... physicians and physicists, social scientists, biologists, mathematicians, philosophers, computer scientists and others… what do you think? Don’t hold back – if beer is necessary for you to address this issue, it can be arranged.
Contact Sarah L (laborde.7@osu.edu)
Interested:
Alireza (alireza.goudarzi at gmail.com)[totally agree with writing down something to figure out what are plausible ways to think about and study this]
Fahad (fahad.khalid@hpi.uni-potsdam.de) [love the topic ... I'm glad someone brought it up ... I might have some ideas to contribute]
Claire (lagesse.claire at gmail.com) [it sounds fascinating... :) ]
Stefan (s.pfenninger12@imperial.ac.uk)
Hiroshi (hashika1@jhmi.edu) [Happy to contribute from a medical and personal point of view]
Sean Hayes(shaye004@ucr.edu)
Note: this doesn’t have to become a formal project, although it could. Let me know if you’re interested in a chat, writing an interdisciplinary dialogue piece, or anything related to this question.
Tradeoffs between division of labor and stability in networks
The Black Queen Hypothesis BQH describes the evolution of functional dependencies in microbial ecosystems. This process results in a subset of a community providing necessary services for the rest of the community (see link). Organisms that can outsource essential functions escape the cost performing these functions and have more resources for growth and reproduction. However, this process makes the ecosystem more delicate, as the destruction of key species can eliminate their crucial service(s) and lead to system collapse. Thus, there is a tradeoff between the stability of a network (in the face of perturbations), and the degree of cooperation (how many tasks can be outsourced). As a result of this tradeoff, we could expect different community types to arise in stable vs. variable environments. There is likely some critical range between these two modes (high vs. low environmental variability), where some mixed strategy is optimal.
This process may have an analogue in the development of multicellular life (vs. free-living single-celled organisms), where each cell type expresses a subset of the genome and provide a specific set of services to the whole (division of labor). This might also be reflected in social or economic networks (higher stability = more cooperative?). A connection could potentially be made to life-history tradeoffs for individual organisms (r vs. k selection - oligotrophs vs. copiotrophs), or in dissipative chemical systems (e.g. Stat-Mech of Self Replication).
Definitely a work in progress, please add your thoughts if you are interested!
Interested:
Sean Gibbons (sgibbons at uchicago dot edu)
Rohan Mehta
How can evolutionary game theory be applied to electricity trading
The interest of this project is the following: how can evolutionary game theory be used to find optimal strategies for consumers and/or producers that bid in the electricity market. Also some real data can be considered.
Contact Blaz
Interested:
Degang Wu
Information Theory of the Heart
The heart is a complex system with simple rules of operation and minimal central control. Under normal conditions, it orchestrates a self-organized, emergent behavior of 2 to 3 billion heart cells to perform sophisticated, well-timed pumping of the blood. Under abnormal conditions, it can lead to sudden cardiac death due to cardiac arrhythmias, which are also emergent, collective behaviors of a large number of heart cells, where each heart cell doesn't necessarily need to be abnormal.
Each heart cell is a dynamic information processing system, which transmits digital information (0 – resting, 1 – excited) in the form of electrical wave. We aim to establish a theoretical basis to quantify information transmission within the heart using information theory and network theory. Our hypothesis is that arrhythmias following heart attack result from an adaptive mechanism to optimize information transmission in abnormal hearts.
If you want to discuss more please contact Hiroshi (hashika1@jhmi.edu).
Interested:
Hiroshi
Flavia
Cells and Software: Is Evolution a Software Engineer?
There appear to be striking similarities between how we design software, and how evolution designed cells. Some of the analogies are:
- The concept of "Encapsulation". In object oriented programs, data inside an object is protected by an interface of functions. Similarly, processes within a cell (intra-cellular signaling cascades) are protected from the extra-cellular messaging activities through membrane-bound receptors acting as the interface.
- Apoptosis (programmed cell death) is similar to proper memory deallocation in programs, while Necrosis is similar to dangling pointers and memory corruption.
- Proteolysis (breaking down of proteins into constituent amino acids) is similar to automatic garbage collection.
There are certain constraints (perhaps physical constraints) on the available solutions in biology. Solutions within this constrained solution space eventually result in the emergence of complex behavior. This emergent behavior has enabled humans to engineer solutions to everyday problems. These artificially engineered solutions are very similar in principal to the solutions that already exist in biological systems.
Are our creative processes ultimately bound by the physical constraints that underlie molecular mechanisms? Or, do we just tend to interpret the phenomena at the molecular level according to our own understanding, which is limited by our senses and neurological processes? Is it all about optimization, and everything else is just a side effect?
Can/do “Patterns” transcend disciplines?
Motifs (biological systems) – Patterns (software). Patterns/motifs transcending biological and software systems could perhaps, fill gaps in our knowledge of biological systems, and help us design better software systems. Deterministic patterns could perhaps indicate what is required for high level functions to emerge from molecular interactions. And perhaps these similarities occur at the interface between low level interaction and emergent phenomena.
So let's further explore biological and software systems, and try to find answers to these questions.
For more information, please contact Fahad (fahad.khalid@hpi.uni-potsdam.de).
Interested:
Fahad
Ernest
Diana
Degang
Stojan
Susceptibility of Fields of Research to Interdisciplinary Influences (network perspective)
Fields of Research are more often than not isolated from one another in terms of their community, jargon, perspective, research programme (in the sense of Lakatos) and their journals and lots more.
This isolation stands in the way of a fruitful merging and interaction of fields. One needs to understand the obstructions. Hence an analysis of the determining factors for 'community inbreeding' is sought after. Eventually also a quantitative measure for the susceptibility of a research field could be formulated.
A clear-cut project could be based on data together with a network type analysis of a precise question around the determining factors. We could look at citation data or journal based data or maybe there is a chance to get hold of data from Jessica's collegues, who works on the diffusion of knowledge.
It would be great also to discuss and gather our ideas and experiences.
Interested
Leo (horstmey@mis.mpg.de )
Jennifer Hellmann
Anna Olson
Lin Li
Stefan Pfenniger
Simple case for studying about “from single-cell to multi-cell / species collaboration”
QUESTION: how single-cell evolves to multi-cell, even they do not have so-called “intelligence”?
How to do:
Let’s imagine that there is a land where resources A, B, C are located, and a kind of creature which need all of these resources to survive (imagine many creatures live in this land).
One surviving strategy is that every creature gathers A, B and C and eat them on its own. But maybe under some condition, specialization would automatically happen (e.g. one creature gather A and another gather B, and then they share).
The goal is to find the necessary condition if possible (we could think out of many sufficient conditions, but finding necessary conditions seems not so easy).
Interested:
Ernest Liu (yu.liu@math.uu.se)
An Analysis of the Hierarchies Present in Modern Economic Theory
The idea of this project is to provide a comprehensive survey of the hierarchical structure of economics (macro -> microeconomics) following the reductionist = constructionist + emergence framework of Anderson. N.B. This equation is my own interpretation of Anderson's paper and is open for discussion. Ideally, we would fist investigate the microfoundations literature of macroeconomics and the possibility for ABM to rectify some of the redundancies therein after which we would reverse the direction and see how, given some 'fundamental' laws of economic behaviour, how we could couple these with emergent phenomena (whatever they may be) to reconstruct the economy at the macro-level.
Interested
Nicolas ( nicolas.scholtes at unamur.be)
The Topological Modeling of Infrastructure Networks
There is some disagreement on the topology of power networks in the literature. There are preferential attachment, small-world and random graph models proposed to explain the topology of power networks. There are caveats associated with each of these generative models. For instance, there is the cost of building new transmission lines that may question the validity of preferential models.
The broad question that we attempt to answer here is:
-Can these previous network models create real-world power networks?
-Can we come up with a better model that can replicate a power network or at least one with similar characteristics?
-What about other infrastructure networks, e.g., natural gas network, water piping networks, etc?
Interested:
Pooya Rezaei
Tom McAndrew