Nash-Minmax Capturing Strategy for Multiagent Pursuit-Evasion Differential Games Under Directed Graphs

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Authors: Ran Shi, Hai-Tao Zhang, Jialuo Li, Fulong Hu, Yuchong Hu, Jiayu Zou
Cited by: 1
References: 29

Abstract

In this article, a heterogeneous multiagent pursuit-evasion (MPE) differential gaming problem is addressed. Therein, the pursuers aim to cooperatively capture the sole escaping evader. The theoretical analytical challenge lies in designing the Nash-minmax gaming strategy for such MPE games under directed graphs with external disturbances. Intra-alliance cooperation (pursuers and their peer neighbors) is regarded as a nonzero-sum game, while interalliance confrontation (multiple pursuers versus one evader) is treated as another zero-sum game. To tackle this issue, a hierarchical gaming framework is established to solve the associated coupled Hamilton-Jacobi-Isaacs (HJI) equation and accordingly derive the associated distributed gaming protocol. Finally, both numerical simulations and lake-based multi-autonomous surface vehicle (ASV) gaming experiments are conducted to verify the effectiveness of the present MPE gaming strategy.

Fields of Study & Subjects

Guidance and Control Systems Extremum Seeking Control Systems Adaptive Dynamic Programming Control

Publication details

Journal / source
IEEE Transactions on Industrial Informatics
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
22
Issue
3
Pages
2402–2411
Publication date
1 January 2026