Prediction, Optimization, and Learning in Repeated Games
Consider a two-player discounted repeated game in which each player optimizes with respect to prior beliefs about his opponent's repeated game strategy. One would like to argue that if beliefs are cautious then players will learn as the game unfolds to predict the continuation path of play. If this conjecture were true then a convergence result due to Kalai and Lehrer would imply that the continuation path would asymptotically resemble the path of a Nash equilibrium. One would thus have constructed a theory which predicts Nash equilibrium as the necessary long-run consequence of optimization by cautious players. This paper points out that there is an obstacle to such a result in the form of a potential conflict between prediction and optimization.
|Date of creation:||11 Apr 1995|
|Date of revision:||14 Feb 1996|
|Note:||Postscript from AMS-LaTeX, 46 pages|
|Contact details of provider:|| Web page: http://126.96.36.199|
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- Lawrence Blume & David Easley, 1993. "Rational Expectations and Rational Learning," Game Theory and Information 9307003, EconWPA.
- Kalai, Ehud & Stanford, William, 1988.
"Finite Rationality and Interpersonal Complexity in Repeated Games,"
Econometric Society, vol. 56(2), pages 397-410, March.
- Ehud Kalai & William Stanford, 1986. "Finite Rationality and Interpersonal Complexity in Repeated Games," Discussion Papers 679, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- Binmore, Ken, 1987. "Modeling Rational Players: Part I," Economics and Philosophy, Cambridge University Press, vol. 3(02), pages 179-214, October.
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