IDEAS home Printed from https://ideas.repec.org/a/spr/eurphb/v76y2010i1p69-85.html
   My bibliography  Save this article

Scale-free memory model for multiagent reinforcement learning. Mean field approximation and rock-paper-scissors dynamics

Author

Listed:
  • I. Lubashevsky

    ()

  • S. Kanemoto

    ()

Abstract

No abstract is available for this item.

Suggested Citation

  • I. Lubashevsky & S. Kanemoto, 2010. "Scale-free memory model for multiagent reinforcement learning. Mean field approximation and rock-paper-scissors dynamics," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 76(1), pages 69-85, July.
  • Handle: RePEc:spr:eurphb:v:76:y:2010:i:1:p:69-85
    DOI: 10.1140/epjb/e2010-00201-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1140/epjb/e2010-00201-8
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    2. Drew Fudenberg & David M. Kreps & Eric S. Maskin, 1990. "Repeated Games with Long-run and Short-run Players," Review of Economic Studies, Oxford University Press, vol. 57(4), pages 555-573.
    3. Drew Fudenberg & Eric Maskin, 1998. "The Folk Theorem for Repeated Games with Discounting and Incomplete Information," Levine's Working Paper Archive 224, David K. Levine.
    Full references (including those not matched with items on IDEAS)

    More about this item

    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:spr:eurphb:v:76:y:2010:i:1:p:69-85. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: http://www.springer.com .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.