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A Partial Folk Theorem for Games with Unknown Payoff Distributions

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  • Thomas Wiseman

Abstract

Repeated games with unknown payoff distributions are analogous to a single decision maker's "multi-armed bandit" problem. Each state of the world corresponds to a different payoff matrix of a stage game. When monitoring is perfect, information about the state is public, and players are sufficiently patient, the following result holds: For any function that maps each state to a payoff vector that is feasible and individually rational in that state, there is a sequential equilibrium in which players experiment to learn the realized state and achieve a payoff close to the one specified for that state. Copyright The Econometric Society 2005.

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File URL: http://hdl.handle.net/10.1111/j.1468-0262.2005.00589.x
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Bibliographic Info

Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 73 (2005)
Issue (Month): 2 (03)
Pages: 629-645

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Handle: RePEc:ecm:emetrp:v:73:y:2005:i:2:p:629-645

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Cited by:
  1. Blume, Andreas & Franco, April Mitchell & Heidhues, Paul, 2011. "Dynamic Coordination via Organizational Routines," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 355, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
  2. Andreas Blume & April Franco & Paul Heidhues, 2006. "Rational Multi-Agent Search," 2006 Meeting Papers 776, Society for Economic Dynamics.
  3. Martin W. Cripps & Jeffrey C. Ely & George J. Mailath & Larry Samuelson, 2006. "Common Learning," Cowles Foundation Discussion Papers 1575R, Cowles Foundation for Research in Economics, Yale University, revised Jun 2007.
    • Martin W. Cripps & Jeffrey C. Ely & George J. Mailath & Larry Samuelson, 2008. "Common Learning," Econometrica, Econometric Society, vol. 76(4), pages 909-933, 07.
  4. Andreas Blume & John Duffy & April Mitchell Franco, 2008. "Decentralized Organizational Learning: An Experimental Investigation," Working Papers 382, University of Pittsburgh, Department of Economics, revised May 2009.
  5. Fudenberg, Drew & Yamamoto, Yuichi, 2011. "Learning from private information in noisy repeated games," Journal of Economic Theory, Elsevier, vol. 146(5), pages 1733-1769, September.
  6. Sonja Brangewitz & Gael Giraud, 2011. "Learning in Infinite Horizon Strategic Market Games with Collateral and Incomplete Information," Working Papers 456, Bielefeld University, Center for Mathematical Economics.
  7. Rosenberg, Dinah & Solan, Eilon & Vieille, Nicolas, 2013. "Strategic information exchange," Games and Economic Behavior, Elsevier, vol. 82(C), pages 444-467.
  8. Yuichi Yamamoto, 2012. "Individual Learning and Cooperation in Noisy Repeated Games," PIER Working Paper Archive 12-044, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  9. Wiseman, Thomas, 2009. "Reputation and exogenous private learning," Journal of Economic Theory, Elsevier, vol. 144(3), pages 1352-1357, May.
  10. Yuichi Yamamoto, 2013. "Individual Learning and Cooperation in Noisy Repeated Games," PIER Working Paper Archive 13-038, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  11. Sylvain Chassang, 2010. "Building Routines: Learning, Cooperation, and the Dynamics of Incomplete Relational Contracts," American Economic Review, American Economic Association, vol. 100(1), pages 448-65, March.
  12. Andreas Blume & April Franco, 2002. "Learning from failure," Staff Report 299, Federal Reserve Bank of Minneapolis.

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