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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
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    References listed on IDEAS

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