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On Adaptive Heuristics that Converge to Correlated Equilibrium

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  • Ayan Bhattacharya

    (Bert W. Wasserman Department of Economics and Finance, Zicklin School of Business, Baruch College, The City University of New York, New York, NY 10010, USA)

Abstract

I study the path properties of adaptive heuristics that mimic the natural dynamics of play in a game and converge to the set of correlated equilibria. Despite their apparent differences, I show that these heuristics have an abstract representation as a sequence of probability distributions that satisfy a number of common properties. These properties arise due to the topological structure of the set of correlated equilibria. The characterizations that I obtain have useful applications in the study of the convergence of the heuristics.

Suggested Citation

  • Ayan Bhattacharya, 2019. "On Adaptive Heuristics that Converge to Correlated Equilibrium," Games, MDPI, vol. 10(1), pages 1-11, January.
    • Handle: RePEc:gam:jgames:v:10:y:2019:i:1:p:6-:d:199803
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    References listed on IDEAS

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    5. Sergiu Hart & Andreu Mas-Colell, 2013. "A Simple Adaptive Procedure Leading To Correlated Equilibrium," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 2, pages 17-46, World Scientific Publishing Co. Pte. Ltd..
    6. Sergiu Hart & Andreu Mas-Colell, 2013. "A General Class Of Adaptive Strategies," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 3, pages 47-76, World Scientific Publishing Co. Pte. Ltd..
    7. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, April.
    8. Foster, Dean P. & Vohra, Rakesh V., 1997. "Calibrated Learning and Correlated Equilibrium," Games and Economic Behavior, Elsevier, vol. 21(1-2), pages 40-55, October.
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