Abstract
Consider a two-player discounted infinitely repeated game. A player's belief is a probability distribution over the opponent's repeated game strategies. This paper shows that, for a large class of repeated games, there are no beliefs that satisfy three properties: learnability, a diversity of belief condition called CSP, and consistency. Loosely, if players learn to forecast the path of play whenever each plays a strategy that the other anticipates (in the sense of being in the support of that player's belief) and if the sets of anticipated strategies are sufficiently rich, then neither anticipates any of his opponent's best responses. This generalizes results in Nachbar (1997).
Original language | English |
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Pages (from-to) | 459-480 |
Number of pages | 22 |
Journal | Econometrica |
Volume | 73 |
Issue number | 2 |
DOIs | |
State | Published - Mar 2005 |
Keywords
- Bayesian learning
- Repeated games