IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v388y2009i23p4893-4900.html
   My bibliography  Save this article

Coevolution of game and network structure with adjustable linking

Author

Listed:
  • Qin, Shao-Meng
  • Zhang, Guo-Yong
  • Chen, Yong

Abstract

Most papers about the evolutionary game on graph assume the statistic network structure. However, in the real world, social interaction could change the relationship among people. And the change of social structure will also affect people’s strategies. We build a coevolution model of prisoner’s dilemma game and network structure to study the dynamic interaction in the real world. Differing from other coevolution models, players rewire their network connections according to the density of cooperation and other players’ payoffs. We use a parameter α to control the effect of payoff in the process of rewiring. Based on the asynchronous update rule and Monte Carlo simulation, we find that, when players prefer to rewire their links to those who are richer, the temptation can increase the cooperation density.

Suggested Citation

  • Qin, Shao-Meng & Zhang, Guo-Yong & Chen, Yong, 2009. "Coevolution of game and network structure with adjustable linking," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(23), pages 4893-4900.
    • Handle: RePEc:eee:phsmap:v:388:y:2009:i:23:p:4893-4900
    DOI: 10.1016/j.physa.2009.08.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437109006645
    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.2009.08.010?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. Li, Gang & Jin, Xiao-Gang & Song, Zhi-Huan, 2012. "Evolutionary game on a stochastic growth network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6664-6673.
    2. Li, Yixiao & Shen, Bin, 2013. "The coevolution of partner switching and strategy updating in non-excludable public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 4956-4965.

    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:388:y:2009:i:23:p:4893-4900. 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.