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Thu, December 13, 2007
Over the past decade, game theorists have made substantial progress in identifying simple learning heuristics that lead to equilibrium behavior without making unrealistic demands on agents information or computational abilities, as is the case in the perfect rationality approach to game theory. Recent research shows that very complex, interactive systems can equilibrate even when agents have virtually no knowledge of the environment in which they are embedded. This talk will survey different approaches to the problem of learning in games, show the various senses in which learning rules converge to equilibrium, and sketch the theoretical limits to what is achievable.