Prediction, Optimization and Learning in Repeated Games
This paper shows that, in many infinitely repeated games, if players optimize with respect to beliefs that satisfy a diversity condition termed neutrality, then each player will choose a strategy that his opponent was certain would not be played. This is an obstacle to formulation of a learning theory in which Nash equilibrium behavior is a necessary long-run consequence of optimization by cautious players.
(This abstract was borrowed from another version of this item.)
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.:
- 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.
- Lawrence Blume & David Easley, 1993. "Rational Expectations and Rational Learning," Game Theory and Information 9307003, EconWPA. Full references (including those not matched with items on IDEAS)
When requesting a correction, please mention this item's handle: RePEc:cla:levarc:576. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (David K. Levine)
If references are entirely missing, you can add them using this form.