Centralized and Decentralized Event-Triggered Nash Equilibrium-Seeking Strategies for Heterogeneous Multi-Agent Systems

This paper addresses the event-triggered Nash equilibrium-seeking problem for non-cooperative games played by heterogeneous multi-agent systems. Unlike homogeneous multi-agent systems, heterogeneous multi-agent systems consist of agents with different dynamic structures, making it difficult to design control schemes and construct event-triggering conditions for such systems. In this paper, a novel centralized event-triggered Nash equilibrium-seeking strategy and a novel decentralized event-triggered Nash equilibrium-seeking strategy are proposed. The corresponding centralized and decentralized event-triggering conditions are derived. The convergence properties of the proposed centralized and decentralized strategies are proved. Further theoretical analyses illustrate that Zeno behavior does not exist under the proposed strategies. Finally, the effectiveness and efficiency of both centralized and decentralized strategies are presented through numerical experiments. The experimental results illustrate that under both strategies, heterogeneous multi-agent systems achieve the Nash equilibrium successfully, and the communication consumption among agents is significantly reduced.

Authors

Institutions

Publication Details

Journal
Mathematics
Published
2025-01-27
DOI
https://doi.org/10.3390/math13030419
Citations
5
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
7.44

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Centralized and Decentralized Event-Triggered Nash Equilibrium-Seeking Strategies for Heterogeneous Multi-Agent Systems

Yunong Zhang, Liu He, Hui Cheng
5 citations
Mathematics
Distributed Control Multi-Agent Systems
7.44
article

Centralized and Decentralized Event-Triggered Nash Equilibrium-Seeking Strategies for Heterogeneous Multi-Agent Systems

Yunong Zhang, Liu He, Hui Cheng
article en
5 citations

Abstract

This paper addresses the event-triggered Nash equilibrium-seeking problem for non-cooperative games played by heterogeneous multi-agent systems. Unlike homogeneous multi-agent systems, heterogeneous multi-agent systems consist of agents with different dynamic structures, making it difficult to design control schemes and construct event-triggering conditions for such systems. In this paper, a novel centralized event-triggered Nash equilibrium-seeking strategy and a novel decentralized event-triggered Nash equilibrium-seeking strategy are proposed. The corresponding centralized and decentralized event-triggering conditions are derived. The convergence properties of the proposed centralized and decentralized strategies are proved. Further theoretical analyses illustrate that Zeno behavior does not exist under the proposed strategies. Finally, the effectiveness and efficiency of both centralized and decentralized strategies are presented through numerical experiments. The experimental results illustrate that under both strategies, heterogeneous multi-agent systems achieve the Nash equilibrium successfully, and the communication consumption among agents is significantly reduced.

MathematicsVol. 13(3)
Sun Yat-sen University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province
Openalex Percentile: Top 3%
Distributed Control Multi-Agent Systems
7.44
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Centralized and Decentralized Event-Triggered Nash Equilibrium-Seeking Strategies for Heterogeneous Multi-Agent Systems — Yunong Zhang, Liu He, et al. · Mathematics (2025) | TGRS Research Map | TGRS