纳什均衡
计算机科学
估计员
ε平衡
趋同(经济学)
数学优化
均衡选择
最佳反应
李雅普诺夫函数
风险主导
计算
数理经济学
博弈论
数学
重复博弈
算法
经济
非线性系统
统计
物理
量子力学
经济增长
出处
期刊:IEEE Transactions on Circuits and Systems Ii-express Briefs
[Institute of Electrical and Electronics Engineers]
日期:2023-03-21
卷期号:70 (9): 3434-3438
被引量:21
标识
DOI:10.1109/tcsii.2023.3259483
摘要
In this brief, we investigate a predefined-time distributed Nash equilibrium seeking problem for a class of noncooperative games under an event-triggered scenario. To achieve fast convergence while reducing the communication and computation costs, a novel distributed Nash equilibrium seeking approach is proposed by applying the gradient play, a consensus-based estimator, and a time base generator (TBG). Different from existing works on Nash equilibrium computation under a bounded convergence time, the design of distributed algorithm in this brief is based on a newly developed TBG. The new TBG is more efficient and convenient than the traditional TBG. By virtue of an adaptive event-triggered rule, the distributed estimators are designed to estimate other players' actions over strongly connected directed graphs. Moreover, the predefined-time convergence analysis of the players' actions to the Nash equilibrium is given based on the Lyapunov stability method. Finally, simulation studies are provided to demonstrate the effectiveness of the constructed TBG and the advantages of the derived strategy.
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