Advanced Search
MyIDEAS: Login to save this paper or follow this series

The Evolution of Cooperation in a Generalized Moran Process

Contents:

Author Info

  • Dai, Darong
Registered author(s):

    Abstract

    In this paper, infinitely repeated prisoner's dilemma game as a benchmark being used to build a new model as the payoff matrix of an evolutionary game dynamics, with the comparative study of game performances between the behavior- pattern “tit for tat” and the behavior-pattern “always defection”, proving that there exists a strictly positive probability, which has a close link with the discount factor, that a single TFT individual can fully invade into a group of ALLD individuals; that is to say, TFT has some kind of evolutionary stability.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://mpra.ub.uni-muenchen.de/40511/
    File Function: original version
    Download Restriction: no

    Bibliographic Info

    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 40511.

    as in new window
    Length:
    Date of creation: 01 Jul 2010
    Date of revision:
    Handle: RePEc:pra:mprapa:40511

    Contact details of provider:
    Postal: Schackstr. 4, D-80539 Munich, Germany
    Phone: +49-(0)89-2180-2219
    Fax: +49-(0)89-2180-3900
    Web page: http://mpra.ub.uni-muenchen.de
    More information through EDIRC

    Related research

    Keywords: IPD; Evolutionary Game Dynamics; Equilibrium Selection;

    Find related papers by JEL classification:

    References

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. Oechssler, Jörg & Riedel, Frank, 1998. "Evolutionary dynamics on infinite strategy spaces," SFB 373 Discussion Papers, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes 1998,68, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Alan Beggs, 2002. "Stochastic evolution with slow learning," Economic Theory, Springer, Springer, vol. 19(2), pages 379-405.
    3. repec:wop:humbsf:1998-68 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:40511. 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: (Ekkehart Schlicht).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 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.