Year: 2024
Type: article
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.
Source: Dynamic Games and Applications
Authors: Andrew Cullen, Tansu Alpcan, Alexander Kalloniatis
Language: English
Topic: Game Theory and Applications
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,190
OpenAlex ID: W4402533593