IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v495y2025ics009630032500058x.html
   My bibliography  Save this article

Environmental feedback promotes cooperation in a spatial prisoner's dilemma game with preferential selection

Author

Listed:
  • Li, Minlan
  • Wang, Chao
  • Han, Yanyan
  • Wang, Si-Yi
  • Wang, Ruiwu

Abstract

The reciprocal influence between the environment and the cooperation level is a ubiquitous reality. Changes in cooperation levels impact environmental quality, while environmental conditions, in turn, affect individual fitness and behavior. Drawing inspiration from this inherent interplay, we investigate the role of environmental feedback on the spatial prisoner's dilemma game. We establish two discrete environmental states by introducing a feedback parameter. Furthermore, we incorporate a more realistic scenario wherein individuals with higher fitness are more likely to be imitated by their neighbors due to preferential selection. Our findings reveal that environmental feedback efficiently fosters cooperation, driven by the preferential selection. Moreover, a specific parameter range is identified in which the enhancement for cooperation is most pronounced. Notably, we observe that environmental feedback alone does not enhance cooperation, a result potentially linked to the nature of feedback formulations employed. These results provide valuable insights into the emergence and evolution of cooperation within complex systems.

Suggested Citation

  • Li, Minlan & Wang, Chao & Han, Yanyan & Wang, Si-Yi & Wang, Ruiwu, 2025. "Environmental feedback promotes cooperation in a spatial prisoner's dilemma game with preferential selection," Applied Mathematics and Computation, Elsevier, vol. 495(C).
    • Handle: RePEc:eee:apmaco:v:495:y:2025:i:c:s009630032500058x
    DOI: 10.1016/j.amc.2025.129331
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S009630032500058X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2025.129331?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.

    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:apmaco:v:495:y:2025:i:c:s009630032500058x. 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: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.