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Learning and Equilibrium

Author

Listed:
  • Drew Fudenberg
  • David K. Levine

    (Department of Economics, Harvard University, Cambridge, Massachusetts
    Department of Economics, Washington University of St. Louis, St. Louis, Missouri)

Abstract
The theory of learning in games explores how, which, and what kind of equilibria might arise as a consequence of a long-run nonequilibrium process of learning, adaptation, and/or imitation. If agents’ strategies are completely observed at the end of each round (and agents are randomly matched with a series of anonymous opponents), fairly simple rules perform well in terms of the agent’s worst-case payoffs, and also guarantee that any steady state of the system must correspond to an equilibrium. If players do not observe the strategies chosen by their opponents (as in extensive-form games), then learning is consistent with steady states that are not Nash equilibria because players can maintain incorrect beliefs about off-path play. Beliefs can also be incorrect because of cognitive limitations and systematic inferential errors.

Suggested Citation

  • Drew Fudenberg & David K. Levine, 2009. "Learning and Equilibrium," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 385-420, May.
    • Handle: RePEc:anr:reveco:v:1:y:2009:p:385-420
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    File URL: http://www.annualreviews.org/doi/abs/10.1146/annurev.economics.050708.142930
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    Keywords

    nonequilibrium dynamics; bounded rationality; Nash equilibrium; self-confirming equilibrium;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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