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Hauptverfasser: Miao, Qiuyu, Wu, Zhigang
Format: Preprint
Veröffentlicht: 2025
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Online-Zugang:https://arxiv.org/abs/2506.11304
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author Miao, Qiuyu
Wu, Zhigang
author_facet Miao, Qiuyu
Wu, Zhigang
contents This paper presents a hybrid adaptive Nash equilibrium solver for distributed multi-agent systems incorporating game-theoretic jump triggering mechanisms. The approach addresses fundamental scalability and computational challenges in multi-agent hybrid systems by integrating distributed game-theoretic optimization with systematic hybrid system design. A novel game-theoretic jump triggering mechanism coordinates discrete mode transitions across multiple agents while maintaining distributed autonomy. The Hybrid Adaptive Nash Equilibrium Solver (HANES) algorithm integrates these methodologies. Sufficient conditions establish exponential convergence to consensus under distributed information constraints. The framework provides rigorous stability guarantees through coupled Hamilton-Jacobi-Bellman equations while enabling rapid emergency response capabilities through coordinated jump dynamics. Simulation studies in pursuit-evasion and leader-follower consensus scenarios demonstrate significant improvements in convergence time, computational efficiency, and scalability compared to existing centralized and distributed approaches.
format Preprint
id arxiv_https___arxiv_org_abs_2506_11304
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Hybrid Adaptive Nash Equilibrium Solver for Distributed Multi-Agent Systems with Game-Theoretic Jump Triggering
Miao, Qiuyu
Wu, Zhigang
Systems and Control
49J15, 91A23, 93A14, 34A60
I.2.11; F.2.2; G.1.6
This paper presents a hybrid adaptive Nash equilibrium solver for distributed multi-agent systems incorporating game-theoretic jump triggering mechanisms. The approach addresses fundamental scalability and computational challenges in multi-agent hybrid systems by integrating distributed game-theoretic optimization with systematic hybrid system design. A novel game-theoretic jump triggering mechanism coordinates discrete mode transitions across multiple agents while maintaining distributed autonomy. The Hybrid Adaptive Nash Equilibrium Solver (HANES) algorithm integrates these methodologies. Sufficient conditions establish exponential convergence to consensus under distributed information constraints. The framework provides rigorous stability guarantees through coupled Hamilton-Jacobi-Bellman equations while enabling rapid emergency response capabilities through coordinated jump dynamics. Simulation studies in pursuit-evasion and leader-follower consensus scenarios demonstrate significant improvements in convergence time, computational efficiency, and scalability compared to existing centralized and distributed approaches.
title A Hybrid Adaptive Nash Equilibrium Solver for Distributed Multi-Agent Systems with Game-Theoretic Jump Triggering
topic Systems and Control
49J15, 91A23, 93A14, 34A60
I.2.11; F.2.2; G.1.6
url https://arxiv.org/abs/2506.11304