IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2607.05932.html

Network games with heterogeneous players

Author

Listed:
  • Wenjie Cao
  • Angel Sanchez
  • Boyu Zhang

Abstract

Real social and economic networks involve individuals with diverse incentives, yet most studies of network games assume homogeneous preferences or few player types. We introduce a general framework for binary choice network games with fully heterogeneous payoff structures. We first show that any such game can be transformed into an equivalent one with conformist, rebel, and stubborn archetypes, preserving equilibria and best response trajectories. We then establish sufficient conditions for pure strategy Nash equilibrium existence and convergence of best response dynamics on arbitrary networks, while proving that equilibria almost surely vanish in large sparse random networks. We further develop a deterministic approximation approach that predicts evolutionary trends and equilibrium strategy frequencies from network homophily and heterophily patterns, without computing equilibria explicitly. Extending the framework to limited information, we prove that dynamics converge either to a unique limited information equilibrium or to a unique stationary distribution, and we derive necessary and sufficient conditions for the existence of the limited information equilibrium. We validate our predictions using Prisoner's Dilemma games on real social networks that incorporate heterogeneous altruism and peer influence. These findings together provide a unified framework for equilibrium existence, evolutionary dynamics, and equilibrium outcome prediction in heterogeneous network games.

Suggested Citation

  • Wenjie Cao & Angel Sanchez & Boyu Zhang, 2026. "Network games with heterogeneous players," Papers 2607.05932, arXiv.org.
  • Handle: RePEc:arx:papers:2607.05932
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2607.05932
    File Function: Latest version
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:arx:papers:2607.05932. 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: arXiv administrators (email available below). General contact details of provider: https://arxiv.org/ .

    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.