IDEAS home Printed from https://ideas.repec.org/a/nos/voprec/y2017id306.html

Whither game theory? Towards a theory oflearning in games

Author

Listed:
  • D. Fudenberg

  • D. 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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • D. Fudenberg & D. K. Levine, 2017. "Whither game theory? Towards a theory oflearning in games," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 5.
    • Handle: RePEc:nos:voprec:y:2017:id:306
    DOI: 10.32609/0042-8736-2017-5-116-135
    as

    Download full text from publisher

    File URL: https://www.vopreco.ru/jour/article/viewFile/306/306
    Download Restriction: no
    File URL: https://libkey.io/10.32609/0042-8736-2017-5-116-135?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. is not listed on IDEAS
    2. Angelos Gkekas & Athina Apostolidou & Artemis Vernadou & Athanasios Kehagias, 2025. "Learning Optimal Strategies in a Duel Game," Games, MDPI, vol. 16(1), pages 1-16, February.
    3. Laslier, Jean-François & Núñez, Matías & Remzi Sanver, M., 2021. "A solution to the two-person implementation problem," Journal of Economic Theory, Elsevier, vol. 194(C).
    4. Nicolas Mäder, 2024. "Financial Crises as a Phenomenon of Multiple Equilibria and How to Select among Them," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(2-3), pages 517-536, March.
    5. 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.
    6. John Asker & Chaim Fershtman & Ariel Pakes, 2024. "The impact of artificial intelligence design on pricing," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 276-304, March.
    7. David Gill & Yaroslav Rosokha, 2024. "Beliefs, Learning, and Personality in the Indefinitely Repeated Prisoner's Dilemma," American Economic Journal: Microeconomics, American Economic Association, vol. 16(3), pages 259-283, August.
    8. 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.
    9. 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).
    10. Matthias Breuer & Eva Labro & Haresh Sapra & Anastasia A. Zakolyukina, 2024. "Bridging Theory and Empirical Research in Accounting," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 62(3), pages 1121-1139, June.
    11. Gillian K. Hadfield & Andrew Koh, 2025. "An Economy of AI Agents," NBER Chapters, in: The Economics of Transformative AI, National Bureau of Economic Research, Inc.
    12. 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.
    13. Mauersberger, Felix & Nagel, Rosemarie, 2025. "Modeling noisy learning in a dynamic oligopoly experiment," Journal of Economic Dynamics and Control, Elsevier, vol. 172(C).
    14. 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.
    15. 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.
    16. Irenaeus Wolff & Dominik Bauer, 2018. "Elusive Beliefs: Why Uncertainty Leads to Stochastic Choice and Errors," TWI Research Paper Series 111, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    17. Aloys Prinz, 2019. "Learning (Not) to Evade Taxes," Games, MDPI, vol. 10(4), pages 1-18, September.
    18. Wang Yijia & Wang Zhijian, 2023. "Pulse in collapse: a game dynamics experiment," Papers 2302.09336, arXiv.org.
    19. 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.
    20. 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.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nos:voprec:y:2017:id:306. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: NEICON (email available below). General contact details of provider: https://www.vopreco.ru .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.