IDEAS home Printed from https://ideas.repec.org/a/spr/dyngam/v15y2025i3d10.1007_s13235-024-00593-4.html
   My bibliography  Save this article

Game-Theoretic Analysis of Adversarial Decision Making in a Complex Socio-Physical System

Author

Listed:
  • Andrew Cullen

    (University of Melbourne)

  • Tansu Alpcan

    (University of Melbourne)

  • Alexander Kalloniatis

    (Defence Science and Technology Group)

Abstract

The growing integration of technology within human processes has significantly increased the difficulty in optimising organisational decision-making, due to the highly coupled and non-linear nature of these systems. This is particularly true in the presence of dynamics for resource competition models between adversarial teams. While game theory provides a conceptual lens for studying such processes, it often struggles with the scale associated with real-world systems. This paper contributes to resolving this limitation through a parallelised variant of the efficient-but-exact nash dominant game pruning framework, which we employ to study the optimal behaviour under adversarial team dynamics parameterised by the so-called networked Boyd–Kuramoto–Lanchester resource competition model. In doing so, we demonstrate a structural bias in competitive systems towards concentrating organisational resources away from regions of competition to ensure resilience.

Suggested Citation

  • Andrew Cullen & Tansu Alpcan & Alexander Kalloniatis, 2025. "Game-Theoretic Analysis of Adversarial Decision Making in a Complex Socio-Physical System," Dynamic Games and Applications, Springer, vol. 15(3), pages 709-728, July.
    • Handle: RePEc:spr:dyngam:v:15:y:2025:i:3:d:10.1007_s13235-024-00593-4
    DOI: 10.1007/s13235-024-00593-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13235-024-00593-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13235-024-00593-4?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:spr:dyngam:v:15:y:2025:i:3:d:10.1007_s13235-024-00593-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.