Learning from Private Information in Noisy Repeated Games

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Learning from Private Information in Noisy Repeated Games

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Title: Learning from Private Information in Noisy Repeated Games
Author: Fudenberg, Drew; Yamamoto, Yuichi

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

Citation: Fudenberg, Drew, and Yuichi Yamamoto. 2011. Learning from private information in noisy repeated games. Journal of Economic Theory 146(5): 1733-1769.
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Abstract: We study the perfect type-contingently public ex-post equilibrium (PTXE) of repeated games where players observe imperfect public signals of the actions played, and both the payoff functions and the map from actions to signal distributions depend on an unknown state. The PTXE payoffs when players are patient are determined by the solutions to a family of linear programming problems. Using this characterization, we develop conditions under which play can be as if the players have learned the state. We provide a sufficient condition for the folk theorem, and a characterization of the PTXE payoffs in games with a known monitoring structure.
Published Version: doi:10.1016/j.jet.2011.03.003
Other Sources: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1703580
Terms of Use: This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:9962008

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  • FAS Scholarly Articles [7374]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
 
 

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