自动化学报2026，Vol.52Issue(1)：108-120,13.DOI:10.16383/j.aas.c250295
通信受限的双网络零和博弈分布式在线优化
Distributed Online Optimization for Two-network Zero-sum Games Under Communication Constraints
摘要
Abstract
This paper investigates the distributed optimization problem in two-network zero-sum games,where the two networks represent two opposing players.Each network consists of a set of agents with time-varying cost func-tions,and the agents optimize the payoff of their network in the game through communication and collaboration.Considering the two communication constrained situations in real optimization scenarios,namely,limited commu-nication resources and limited information feedback,a distributed online optimization algorithm based on event-triggered communication and two-point Bandit feedback is designed,and the performance of the algorithm is evalu-ated using the dynamic Nash equilibrium regret.Under certain assumptions,a sublinear dynamic Nash equilibrium regret bound relative to the total number of game iterations is established,thereby validating the effectiveness of the algorithm.Additionally,the designed algorithm is extended to a multi-epoch version,and a sublinear dynamic Nash equilibrium regret bound is also established.Finally,a simulation example involving a bilinear matrix game is provided to further verify the performance of the two designed algorithms.关键词
零和博弈/分布式在线优化/动态纳什均衡遗憾/Bandit反馈/事件触发通信Key words
zero-sum games/distributed online optimization/dynamic Nash equilibrium regret/Bandit feedback/event-triggered communication引用本文复制引用
廖岚,于湛,袁德明,张保勇,徐胜元..通信受限的双网络零和博弈分布式在线优化[J].自动化学报,2026,52(1):108-120,13.基金项目
国家自然科学基金(62373190,62273181,62221004,12401123),香港特别行政区研究资助局(HKBU 12301424),江苏省研究生科研与实践创新计划(KYCX24_0673)资助 Supported by National Natural Science Foundation of China(62373190,62273181,62221004,12401123),Research Grants Council of Hong Kong Special Administrative Region(HKBU 12301424),and Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_0673) （62373190,62273181,62221004,12401123）
