IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v655y2024ics0378437124007234.html
   My bibliography  Save this article

Steering cooperation: Adversarial attacks on prisoner’s dilemma in complex networks

Author

Listed:
  • Takemoto, Kazuhiro

Abstract

This study examines the application of adversarial attack concepts to control the evolution of cooperation in the prisoner’s dilemma game in complex networks. Specifically, it proposes a simple adversarial attack method that drives players’ strategies towards a target state by adding small perturbations to social networks. The proposed method is evaluated on both model and real-world networks. Numerical simulations demonstrate that the proposed method can effectively promote cooperation with significantly smaller perturbations compared to other techniques. Additionally, this study shows that adversarial attacks can also be useful in inhibiting cooperation (promoting defection). The findings reveal that adversarial attacks on social networks can be potent tools for both promoting and inhibiting cooperation, opening new possibilities for controlling cooperative behavior in social systems while also highlighting potential risks.

Suggested Citation

  • Takemoto, Kazuhiro, 2024. "Steering cooperation: Adversarial attacks on prisoner’s dilemma in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 655(C).
  • Handle: RePEc:eee:phsmap:v:655:y:2024:i:c:s0378437124007234
    DOI: 10.1016/j.physa.2024.130214
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124007234
    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.2024.130214?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:phsmap:v:655:y:2024:i:c:s0378437124007234. 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.