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Adversarial decisions on complex dynamical systems using game theory

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  • Cullen, Andrew C.
  • Alpcan, Tansu
  • Kalloniatis, Alexander C.

Abstract

We apply computational Game Theory to a unification of physics-based models that represent decision-making across a number of agents within both cooperative and competitive processes. Here the competitors try to both positively influence their own returns, while negatively affecting those of their competitors. Modelling these interactions with the so-called Boyd–Kuramoto–Lanchester (BKL) complex dynamical system model yields results that can be applied to business, gaming and security contexts. This paper studies a class of decision problems on the BKL model, where a large set of coupled, switching dynamical systems are analysed using game-theoretic methods.

Suggested Citation

  • Cullen, Andrew C. & Alpcan, Tansu & Kalloniatis, Alexander C., 2022. "Adversarial decisions on complex dynamical systems using game theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    • Handle: RePEc:eee:phsmap:v:594:y:2022:i:c:s0378437122000826
    DOI: 10.1016/j.physa.2022.126998
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    References listed on IDEAS

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