This book collects the essential existing results in the fast-paced  field of learning and evolutionary game theory together with new work by  two leaders in the field. It will be essential to anyone doing  theoretical work on learning and games or using evoultionary game theory  in applied work. -- Larry Samuelson, Antoine Augustin Cournot Professor  of Economics, University of Wisconsin    In economics, most noncooperative game theory has focused on equilibrium  in games, especially Nash equilibrium and its refinements. The  traditional explanation for when and why equilibrium arises is that it  results from analysis and introspection by the players in a situation  where the rules of the game, the rationality of the players, and the  players' payoff functions are all common knowledge. Both conceptually  and empirically, this theory has many problems.    In  The Theory of Learning in Games  Drew Fudenberg and David  Levine develop an alternative explanation that equilibrium arises as the  long-run outcome of a process in which less than fully rational players  grope for optimality over time. The models they explore provide a  foundation for equilibrium theory and suggest useful ways for economists  to evaluate and modify traditional equilibrium concepts.

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