Almost-Rational Learning of Nash Equilibrium without Absolute Continuity
AbstractIf players learn to play an infinitely repeated game using Bayesian learning, it is known that their strategies eventually approximate Nash equilibria of the repeated game under an absolute-continuity assumption on their prior beliefs.� We suppose here that Bayesian learners do not start with such a "grain of truth", but with arbitrarily low probability they revise beliefs that are performing badly.� We show that this process converges in probability to a Nash equilibrium of the repeated game.
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Bibliographic InfoPaper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 602.
Date of creation: 01 Apr 2012
Date of revision:
Repeated games; Nash equilibrium; Rational learning; Bayesian learning; Absolute continuity;
Find related papers by JEL classification:
- C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-05-02 (All new papers)
- NEP-EVO-2012-05-02 (Evolutionary Economics)
- NEP-GTH-2012-05-02 (Game Theory)
- NEP-HPE-2012-05-02 (History & Philosophy of Economics)
- NEP-MIC-2012-05-02 (Microeconomics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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Game Theory and Information, EconWPA
9504001, EconWPA, revised 14 Feb 1996.
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