From Santa Fe Institute Events Wiki
- Kate Anderson, Economics, U. of Michigan [email]
- Michael Aylward, Economics, U. of Michigan [email]
- Christopher Cameron, Sociology, Cornell [email]
- Chris Fowler, Geography, U. of Washington[email]
- Sera Linardi, Social Science, Cal Tech [email]
- Tobias Lorenz, Philosophy, Stuttgart University [email]
- Vincent Matossian, Computer Engineering, Rutgers [email]
- Jolie Martin, Information Technology and Management, Harvard Business School [email]
- Ryan Muldoon, Philosophy, U. of Pennsylvania [email]
- Robi Ragan, Political Science, U. of Georgia [email]
- Rob Axtell, Computational Social Science, George Mason U. and SFI.
- Samuel Bowles, Economics, U. Massachusetts (emeritus), U. of Sienna, and SFI.
- Jennifer Dunne, Ecology, SFI.
- Charles Efferson, Evolutionary Ecology, SFI and Zurich.
- John H. Miller (co- director), Economics, Carnegie Mellon University and SFI.
- Scott E. Page (co-director), Economics, U. of Michigan and SFI.
- Jon Wilkins, Theoretical Biology, SFI.
Each student began a research project during the two-week workshop. Below are brief descriptions of these various projects. These projects will form the basis for dissertation chapters and/or journal articles.
Kate Anderson, Economics, U. of Michigan (email@example.com).
Kate analyzes matching with endogenous preferences, for example, a world in which professors want to join high quality academic departments, and in the process of doing so change the quality of the departments. Agents have endogenous preferences tied to the "ranking" of the department they join and an exogenous preference that is due to an innate preference ordering over the departments. She finds that as agents weight exogenous preferences more, there is a nonlinear transformation whereby groups tend to equilibrate in quality and agents tend to get their top choices. She also finds that "tiers" of schools emerge and that rankings tend to lock in quite early.
Michael Aylward, Economics, U. of Michigan (firstname.lastname@example.org).
Michael is exploring an agent's search for knowledge. In his model, agents search the world for potential pieces of knowledge (operationalized by draws on a distribution). Knowledge may potentially have value on its own, or it may need to be combined with other pieces of knowledge to gain value. Agents must decide whether to consume knowledge now or to save it for possible future use, all the while attempting to discover the underlying process that makes any particular piece of knowledge potentially valuable.
Christopher Cameron, Sociology, Cornell (email@example.com).
Chris employs an agent-based model to understand turn taking across a one lane bridge. The problem, inspired by an actual bridge in Ithaca, New York, has cars approaching either end of a one lane bridge without any signs or signals to coordinate the crossing. Drivers are modeled as having a decision zone in which they must decide whether to follow a previous car or to move onto the empty bridge, as possible.
Chris Fowler, Geography, U. of Washington (firstname.lastname@example.org).
Chris takes one of Krugman's models of economic geography and instantiates it in a more realistic and dynamic setting. Firms, manufacturing workers, and agricultural workers seek out geographic locations so as to increase their utilities. In his modeling, he uses agent-based objects and introduces more realistic market mechanisms. He finds that once workers have sufficient mobility, a variety of stable equilibria are likely, though they often deviate in significant ways from those commonly observed. Currently he is trying to "dock" his agent-based model to the existing theoretical models to gain a deeper understanding of both.
Sera Linardi, Social Science, Cal Tech (email@example.com).
Sera is comparing voting mechanisms that are used to aggregate information. As benchmarks for understanding such mechanisms she uses human experiments, the theory of rational agents, and an agent-based model. The theory based on rational agents makes quite striking predictions that often differ from the experimental observations. Her agent based model uses two types of agents: rational and random. She finds that as the underlying states of the world become harder to distinguish from one another, the performance of different mixes of agent types in the population reverses. Moreover, the artificial agents behavior tends to corresponds to that of human subjects as problems become more difficult.
Tobias Lorenz, Philosophy, Stuttgart University (firstname.lastname@example.org).
Toby considers the link between guaranteeing a basic income to all and unemployment. He uses an economic model of labor supply as the basis for his modeling, and proceeds by allowing heterogeneous agents to interact with a labor market under different policy arrangements. He finds that the impact of a guaranteed income program is closely tied to the heterogeneity of the population. Moreover, if you allow agents that are close to one another to influence each other's preferences, you can easily get clusters of unemployment taking over parts of the system.
Vincent Matossian, Computer Engineering, Rutgers (email@example.com).
Vincent is evolving networks with arbitrary structural properties. He uses simulated annealing techniques to evolve networks that optimize sets of network attributes (here, measures of transitivity, assortivity, and entropy). He finds that this technique is capable of simultaneously manipulating these measures and driving each of them toward the unconstrained univariate optima. The next step is to use a similar methodology to "grow" graphs, based on simple generation principles, that embody certain final attributes.
Jolie Martin, Information Technology and Management, Harvard Business School (firstname.lastname@example.org).
Jolie is investigating systems that aggregate the opinions of others to improve individual decision making. Advances in information systems have made such ratings widely available across products such as books and movies. Her model assumes that there are clusters of individuals with similar preferences across goods. She finds that strategies evolve into two camps where either individuals rate everything or nothing. The proportion of these strategies in the population can be tied to the individual's cost of rating goods and the size of the underlying preference clusters. She also finds that the amount of ratings activity can fluctuate over time, resulting in interesting strategic dynamics as observed clusters become more or less difficult to identify.
Ryan Muldoon, Philosophy, U. of Pennsylvania (email@example.com).
Ryan is analyzing the influence of diversity on social contracts. Agents live on a two-dimensional landscape that represents potential social contracts, and must coordinate on a contract that is close to their ideal point yet recognizes the value of having a diversity of other types included in the group. He finds that the social product increases and the number of social contracts decreases as agents are able to extend their searches. Furthermore, social product increases when diversity traits are closely correlated with underlying preferences. Agents that are more willing to consider alternative social contracts and compromise their positions tend, on average, to do better in such models.
Robi Ragan, Political Science, U. of Georgia (firstname.lastname@example.org).
Robi wants to create an "artificial" congress to understand better the complex adaptive behavior of political institutions. The project begins by replicating three core models in political science that embrace issues surrounding distribution, information, and party alliances. He found that agents directed by simple learning rules behave in a manner consistent with the existing models. He is currently adding more "complexity" to the behavioral repertoire of his congressional agents to investigate new issues as well as extend the investigation of existing models.