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

被引：4

作者：

Zhang, Tao ^{[1
]}

Zhu, Yiji ^{[1
]}

Ma, Dongying ^{[2
]}

Li, Chaoyong ^{[1
]}

Wang, Xiaodong ^{[2
]}

机构：

[1] Zhejiang Univ, Coll Elect Engn, Hangzhou 310027, Peoples R China

[2] Beijing Inst Elect Syst Engn, Beijing 100854, Peoples R China

来源：

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS | 2024年 / 60卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Games; Approximation algorithms; Computational modeling; Military computing; Analytical models; Nash equilibrium; Task analysis; Game theory; search algorithm; swarm operation; COORDINATED TARGET ASSIGNMENT; ALGORITHM; APPROXIMATION;

D O I：

10.1109/TAES.2024.3361436

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

The decision and control problem for swarm operations is crucial for autonomous military conflict management. In this article, the underlying decision and control problem is treated as a noncooperative 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 epsilon-Nash with guaranteed computational efficiency, and is well suited for the swarm conflict. Simulation results verified the effectiveness of the proposed solutions.

引用

页码：3108 / 3120

页数：13

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