Group-Based Joint Strategy Fictitious Play With Inertia for Potential Games

• 成果类型: Article
• 署名作者: Wang, Yanfei; Li, Yiliang; Feng, Jun-e
• 署名单位: Shandong University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2026.3670755
• 发表日期: 2026
• 关键词: Nash equilibrium seeking; Intergroup conflict

摘要

We propose a novel fictitious-play-based learning algorithm, called group-based joint strategy fictitious play (GJSFP) with inertia, to seek group-based Nash equilibria of group-based generalized ordinal potential games. The proposed GJSFP with inertia enables group-based Nash equilibria to possess an absorption property, and allows group-based generalized ordinal potential games to converge to group-based Nash equilibria under some certain conditions. Notably, the convergence of group-based generalized ordinal potential games without additional conditions can be guaranteed under a fading memory GJSFP with inertia. For group-based networked potential games, fading memory GJSFP with inertia ensures that such games converge to a profile that is both a group-based Nash equilibrium and an individual-based Nash equilibrium.