The Theory of Learning in Games

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MIT Press, 1998 - Business & Economics - 276 pages
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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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Contents

Introduction
1
Fictitious Play
29
Replicator Dynamics and Related Deterministic Models
51
Stochastic Fictitious Play and MixedStrategy Equilibria
101
Adjustment Models with Persistent Randomness
137
ExtensiveForm Games and Selfconfirming Equilibrium
175
Nash Equilibrium Large Population Models and Mutations
201
Sophisticated Learning
231
References
266
Copyright

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Page 267 - Schapire. A decision theoretic generalization of on-line learning and an application to boosting.

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About the author (1998)

David K. Levine is John H. Biggs Distinguished Professor of Economics at Washington University, St. Louis.

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