Abstract.
In Nachbar [20] and, more definitively, Nachbar [22], I argued that, for a large class of discounted infinitely repeated games of complete information (i.e. stage game payoff functions are common knowledge), it is impossible to construct a Bayesian learning theory in which player beliefs are simultaneously weakly cautious, symmetric, and consistent. The present paper establishes a similar impossibility theorem for repeated games of incomplete information, that is, for repeated games in which stage game payoff functions are private information.
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Received: 15 October 1997/Accepted: 17 March 1999
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Nachbar, J. Bayesian learning in repeated games of incomplete information. Soc Choice Welfare 18, 303–326 (2001). https://doi.org/10.1007/PL00007181
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DOI: https://doi.org/10.1007/PL00007181