IDEAS home Printed from https://ideas.repec.org/a/wsi/ijmpcx/v31y2020i11ns0129183120501624.html
   My bibliography  Save this article

The evolution of extortion strategy in the kagome lattice

Author

Listed:
  • Qian Zhao

    (School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China)

  • Yajun Mao

    (School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China)

  • Zhihai Rong

    (School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China)

Abstract

The extortion strategy can let its surplus exceed its opponents by a fixed percentage, hence the influence of extortion strategy in a population games has drawn wide attention. In this paper, we study the evolution of extortion strategy with unconditional cooperation and unconditional defection strategies in the Kagome lattice with abundant triangles. Our investigation shows that the extortion strategy can act as catalysts to promote the evolution of cooperation in the networked Prisoner’s Dilemma game. Moreover, proper strength of extortion slope can improve the living environment of the cooperators, thus they enhance cooperation level in the network. Moreover, proper strength of extortion can not only enhance the cooperation level, but also delay the extinction of cooperation. The underlying overlapping triangles help individuals form cooperation cliques that play crucial roles for the evolution of cooperation in those lattices.

Suggested Citation

  • Qian Zhao & Yajun Mao & Zhihai Rong, 2020. "The evolution of extortion strategy in the kagome lattice," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 31(11), pages 1-10, November.
  • Handle: RePEc:wsi:ijmpcx:v:31:y:2020:i:11:n:s0129183120501624
    DOI: 10.1142/S0129183120501624
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0129183120501624
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S0129183120501624?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. Lee, Hsuan-Wei & Cleveland, Colin & Szolnoki, Attila, 2022. "Mercenary punishment in structured populations," Applied Mathematics and Computation, Elsevier, vol. 417(C).

    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:wsi:ijmpcx:v:31:y:2020:i:11:n:s0129183120501624. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijmpc/ijmpc.shtml .

    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.