Title: Learning to Coordinate: Experiments with Artificial and Real Agents
Abstract: How do agents facing coordination problems select from among multiple equilibrium possibilities? This question has been addressed in social science research using theoretical models, agent-based simulations and human subject experiments. Yet surprisingly, there is little interaction between these different methods, particularly between agent-based models and laboratory experiments. In this talk, I will make the case that agent based models and human subject experiments are complementary tools for the analysis of coordination problems as well as other topics. I will provide two examples of coordination problems, one at the micro-level and one at the macro-level, showing how experiments with real and artificial agents can be profitably combined.
John Duffy is Professor of Economics at the University of California, Irvine. His research concerns the micro-foundations of aggregate phenomena such as monetary exchange, oting and information aggregation and social norms of behavior. Duffy addresses these topics using models, laboratory experiments and agent-based simulations. His research has appeared in the leading economics journals and has been funded by the U.S. National Science Foundation.