Social Power Games for Parallel Friedkin-Johnsen Models

• 成果类型: Article
• 署名作者: Wang, Lingfei; Xing, Yu; Huang, Shijie; Altafini, Claudio; Johansson, Karl Henrik
• 署名单位: Royal Institute of Technology; Delft University of Technology; Linkoping University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2025.3631717
• 发表日期: 2026
• 关键词: opinion dynamics; stubborn agents; equilibrium; networks; CONVERGENCE; EXISTENCE; EVOLUTION; TUTORIAL

摘要

In this article, we consider a strategic game played by a group of agents on a set of opinion dynamics models. The models are all Friedkin-Johnsen (FJ) models, which are independent of each other (we call them parallel FJ models). The task of an agent is to maximize her overall social power by allocating a given budget of stubbornness across the parallel FJ models. For this game, the cost function is shown to be convex in the action profile set, but discontinuous at some boundary points when for some FJ model only one agent is stubborn (i.e., assigning nonzero stubbornness in the FJ model). Despite the discontinuity, an Nash equilibrium is shown to exist, but is not necessarily unique. Some sufficient conditions that can guarantee the uniqueness are proposed, relying on the strictly monotone pseudogradient mappings associated to the game. The conditions are applied to complete graphs with rank-1 weight matrices, for which the link weights are unequal for different agents and on different FJ models. Moreover, for the complete graph case, given the actions of the other agents, the best response of each agent is analytically characterized.