Work

Accelerated Nash equilibrium seeking algorithm with local memory for two-subnetwork zero-sum games

Year: 2025

Type: article

Abstract: This paper focuses on the distributed Nash equilibrium seeking problem for two-subnetwork zero-sum games. We first utilize the local memory information to design an accelerated algorithm in a distributed manner for the two-subnetwork zero-sum game. Then, we present a sufficient condition for the exponential convergence of the proposed algorithm with local memory, which can ensure the agents’ states converge exponentially to the unique Nash equilibrium. One of the advantages of the proposed algorithm is that the communication requirements are weaker than those of the existing ones. Finally, we use numerical experiments to demonstrate that the convergence speed of the proposed algorithm can be accelerated if the appropriate memory factor is selected and is faster than that of the existing ones.

Source: Chaos Solitons & Fractals

DOI: 10.1016/j.chaos.2025.117103

Authors: Jiuan Gao, Daning Lei, Mingxing Qin, Jianxiang Xi, Yuanshi Zheng

Institutions: PLA Rocket Force University of Engineering, Xidian University

Language: English

Topic: Distributed Control Multi-Agent Systems

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,970

Funders: National Natural Science Foundation of China, Key Research and Development Projects of Shaanxi Province