IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v375y2007i1p323-335.html
   My bibliography  Save this article

Evolutionary Markovian strategies in 2×2 spatial games

Author

Listed:
  • Fort, H.
  • Sicardi, E.

Abstract

Evolutionary spatial 2×2 games between heterogeneous agents are analyzed using different variants of cellular automata (CA). Agents play repeatedly against their nearest neighbors 2×2 games specified by a rescaled payoff matrix with two parameters. Each agent is governed by a binary Markovian strategy (BMS) specified by four conditional probabilities [pR, pS, pT, pP] that take values 0 or 1. The initial configuration consists in a random assignment of “strategists” among the 24= 16 possible BMS. The system then evolves within strategy space according to the simple standard rule: each agent copies the strategy of the neighbor who got the highest payoff. Besides on the payoff matrix, the dominant strategy—and the degree of cooperation—depend on (i) the type of the neighborhood (von Neumann or Moore); (ii) the way the cooperation state is actualized (deterministically or stochastically); and (iii) the amount of noise measured by a parameter ε. However a robust winner strategy is [1,0,1,1].

Suggested Citation

  • Fort, H. & Sicardi, E., 2007. "Evolutionary Markovian strategies in 2×2 spatial games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(1), pages 323-335.
    • Handle: RePEc:eee:phsmap:v:375:y:2007:i:1:p:323-335
    DOI: 10.1016/j.physa.2006.09.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437106009885
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2006.09.004?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
    ---><---

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

    Citations

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


    Cited by:

    1. Ohdaira, Tetsushi, 2024. "The universal probabilistic reward based on the difference of payoff realizes the evolution of cooperation," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    2. Tetsushi Ohdaira & Takao Terano, 2009. "Cooperation in the Prisoner's Dilemma Game Based on the Second-Best Decision," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(4), pages 1-7.
    3. Ziaukas, Pranas & Ragulskis, Tautvydas & Ragulskis, Minvydas, 2014. "Communication scheme based on evolutionary spatial 2×2 games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 177-188.
    4. Tetsushi Ohdaira, 2021. "Cooperation evolves by the payoff-difference-based probabilistic reward," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(11), pages 1-8, November.

    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:eee:phsmap:v:375:y:2007:i:1:p:323-335. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.