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Whither Game Theory? Towards a Theory of Learning in Games

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  • Drew Fudenberg
  • David K. Levine

Abstract

Game theory has been a huge success in economics. Many important questions have been answered, and game theoretic methods are now central to much economic investigation. We suggest areas where further advances are important, and argue that models of learning are a promising route for improving and widening game theory's predictive power while preserving the successes of game theory where it already works well. We emphasize in particular the need for better understanding of the speed with which learning takes place.

Suggested Citation

  • Drew Fudenberg & David K. Levine, 2016. "Whither Game Theory? Towards a Theory of Learning in Games," Journal of Economic Perspectives, American Economic Association, vol. 30(4), pages 151-170, Fall.
    • Handle: RePEc:aea:jecper:v:30:y:2016:i:4:p:151-70
    Note: DOI: 10.1257/jep.30.4.151
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    3. Finigan, Duncan & Mills, Brian M. & Stone, Daniel F., 2020. "Pulling starters," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 89(C).
    4. Ren Yang & Yuancheng Lin, 2022. "Rural spatial transformation and governance from the perspective of land development rights: A case study of Fenghe village in Guangzhou," Growth and Change, Wiley Blackwell, vol. 53(3), pages 1102-1121, September.
    5. Wang Yijia & Wang Zhijian, 2023. "Pulse in collapse: a game dynamics experiment," Papers 2302.09336, arXiv.org.
    6. Cason, Timothy N. & Mui, Vai-Lam, 2019. "Individual versus group choices of repeated game strategies: A strategy method approach," Games and Economic Behavior, Elsevier, vol. 114(C), pages 128-145.
    7. Irenaeus Wolff & Dominik Bauer, 2018. "Elusive Beliefs: Why Uncertainty Leads to Stochastic Choice and Errors," TWI Research Paper Series 111, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    8. Emilio Calvano & Giacomo Calzolari & Vincenzo Denicolò & Sergio Pastorello, 2020. "Artificial Intelligence, Algorithmic Pricing, and Collusion," American Economic Review, American Economic Association, vol. 110(10), pages 3267-3297, October.
    9. Emilio Calvano & Giacomo Calzolari & Vincenzo Denicolò & Sergio Pastorello, 2019. "Algorithmic Pricing What Implications for Competition Policy?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 55(1), pages 155-171, August.
    10. Gilboa, Itzhak & Minardi, Stefania & Samuelson, Larry, 2020. "Theories and cases in decisions under uncertainty," Games and Economic Behavior, Elsevier, vol. 123(C), pages 22-40.
    11. Philipp Denter & John Morgan & Dana Sisak, 2022. "Showing Off or Laying Low? The Economics of Psych-outs," American Economic Journal: Microeconomics, American Economic Association, vol. 14(1), pages 529-580, February.
    12. Aloys Prinz, 2019. "Learning (Not) to Evade Taxes," Games, MDPI, vol. 10(4), pages 1-18, September.
    13. David Gill & Yaroslav Rosokha, 2023. "Beliefs, learning, and personality in the indefinitely repeated prisoner's dilemma," Purdue University Economics Working Papers 1332, Purdue University, Department of Economics.
    14. Pablo S. Castro & Ajit Desai & Han Du & Rodney Garratt & Francisco Rivadeneyra, 2021. "Estimating Policy Functions in Payments Systems Using Reinforcement Learning," Staff Working Papers 21-7, Bank of Canada.

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    More about this item

    JEL classification:

    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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