Learning to Play Bayesian Games

DSpace/Manakin Repository

Learning to Play Bayesian Games

Citable link to this page

 

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

Note: Order does not necessarily reflect citation order of authors.

Citation: Dekel, Eddie, Drew Fudenberg, and David K. Levine. 2004. Learning to play Bayesian games. Games and Economic Behavior 46, no. 2: 282-303.
Full Text & Related Files:
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
Downloads of this work:

Show full Dublin Core record

This item appears in the following Collection(s)

 
 

Search DASH


Advanced Search
 
 

Submitters