IDEAS home Printed from https://ideas.repec.org/a/inm/ormoor/v48y2023i2p914-941.html
   My bibliography  Save this article

Multiagent Online Learning in Time-Varying Games

Author

Listed:
  • Benoit Duvocelle

    (Department of Quantitative Economics, Maastricht University, NL–6200 MD Maastricht, Netherlands)

  • Panayotis Mertikopoulos

    (Université Grenoble Alpes, CNRS, Inria, Grenoble INP, LIG, 38000 Grenoble, France; Criteo AI Lab, 38130 Echirolles, France)

  • Mathias Staudigl

    (Department of Advanced Computing Sciences, Maastricht University, NL–6200 MD Maastricht, Netherlands)

  • Dries Vermeulen

    (Department of Quantitative Economics, Maastricht University, NL–6200 MD Maastricht, Netherlands)

Abstract

We examine the long-run behavior of multiagent online learning in games that evolve over time. Specifically, we focus on a wide class of policies based on mirror descent, and we show that the induced sequence of play (a) converges to a Nash equilibrium in time-varying games that stabilize in the long run to a strictly monotone limit, and (b) it stays asymptotically close to the evolving equilibrium of the sequence of stage games (assuming they are strongly monotone). Our results apply to both gradient- and payoff-based feedback—that is, when players only get to observe the payoffs of their chosen actions.

Suggested Citation

  • Benoit Duvocelle & Panayotis Mertikopoulos & Mathias Staudigl & Dries Vermeulen, 2023. "Multiagent Online Learning in Time-Varying Games," Mathematics of Operations Research, INFORMS, vol. 48(2), pages 914-941, May.
    • Handle: RePEc:inm:ormoor:v:48:y:2023:i:2:p:914-941
    DOI: 10.1287/moor.2022.1283
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/moor.2022.1283
    Download Restriction: no
    File URL: https://libkey.io/10.1287/moor.2022.1283?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
    ---><---

    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:inm:ormoor:v:48:y:2023:i:2:p:914-941. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.