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Toward Rapid and Optimal Strategy for Swarm Conflict: A Computational Game Approach

Tao Zhang, Zhu Yiji, Dongying Ma, Chaoyong Li, Xiaodong Wang

2024IEEE Transactions on Aerospace and Electronic Systems15 citationsDOI

Abstract

The decision and control problem for swarm operations is crucial for autonomous military conflict management. In this paper, the underlying decision and control problem is treated as a non-cooperative game problem, in which the underlying target assignment problem is generalized to be a graph-theoretic problem. We introduce an algorithm to seek the desired Nash equilibrium with the help of the parallel maximum weight matching algorithm. Then, we prove that the proposed solution is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula> -Nash with guaranteed computational efficiency, and is well suited for the swarm conflict. Simulation results verified the effectiveness of the proposed solutions.

Topics & Concepts

Swarm behaviourMathematical optimizationNash equilibriumGame theoryNotationAssignment problemComputer scienceGeneralized assignment problemMatching (statistics)Theoretical computer scienceMathematicsMathematical economicsArithmeticStatisticsMilitary Defense Systems AnalysisGuidance and Control SystemsDistributed Control Multi-Agent Systems
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