非平衡有向图上具有异质一般线性动力学的多联盟博弈的规定时间纳什均衡寻求。

IF 10.5 1区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

IEEE Transactions on Cybernetics Pub Date : 2025-09-16 DOI:10.1109/tcyb.2025.3598948

Yiyang Chen,Xiaoduo Li,Zhi Feng,Yongzhao Hua,Xiwang Dong

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引用次数: 0

摘要

本文研究了非平衡有向图上具有异质一般线性动力学的多联盟博弈的纳什均衡问题。联盟可以被看作是一个虚拟的参与者，但真正的决策者是实际的参与者自己，他们只能使用自己的成本函数。为了处理不平衡有向图，估计了左特征向量，并利用时间传递方法说明了其规定的时间收敛性。然后设计了NE搜索部分和输出调节部分来适应参与者的动态。为了避免利用出度信息，选择了辅助向量的初始值。分析了闭环系统的稳态，并利用李雅普诺夫方法证明了系统的时间收敛性。最后，给出了移动传感器连接博弈和电力市场博弈的仿真结果，验证了算法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Prescribed-Time Nash Equilibrium Seeking for Multicoalition Games With Heterogeneous General Linear Dynamics Over Unbalanced Digraphs.

This article investigates the Nash equilibrium (NE) seeking problems for multicoalition games with heterogeneous general linear dynamics over unbalanced digraphs. The coalition can be regarded as a virtual player but the true decision-makers are the actual players themselves which can only access to their own cost functions. To deal with the unbalanced digraphs, the left eigenvector is estimated and its prescribed-time convergence is illuminated with the time transfer approach. Then the NE seeking part and the output regulation part are designed to adapt the dynamics of the players. The initial values of the auxiliary vectors are selected to avoid utilizing the out-degree information. The steady state of the closed-loop system is analyzed and the prescribed-time convergence is proved based on the Lyapunov method. Finally, the simulation results of both the mobile sensor connectivity game and the electricity market game are presented to show the effectiveness of the proposed algorithm.

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来源期刊

IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS

CiteScore

25.40

自引率

11.00%

发文量

1869

期刊介绍： The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.