Learning to Play Bayesian Games

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Learning to Play Bayesian Games

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Title: Learning to Play Bayesian Games
Author: Levine, David; Dekel, Eddie; Fudenberg, Drew

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Citation: Dekel, Eddie, Drew Fudenberg, and David K. Levine. 2004. Learning to play Bayesian games. Games and Economic Behavior 46, no. 2: 282-303.
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Abstract: This paper discusses the implications of learning theory for the analysis of games with a move by Nature. One goal is to illuminate the issues that arise when modeling situations where players are learning about the distribution of Nature's move as well as learning about the opponents' strategies. A second goal is to argue that quite restrictive assumptions are necessary to justify the concept of Nash equilibrium without a common prior as a steady state of a learning process.
Published Version: http://dx.doi.org/10.1016/S0899-8256(03)00121-0
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:3200612
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