Single-Timescale Distributed GNE Seeking for Aggregative Games Over Networks via Forward-Backward Operator Splitting

• 成果类型: Article
• 署名作者: Gadjov, Dian; Pavel, Lacra
• 署名单位: University of Toronto
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2020.3015354
• 发表日期: 2021
• 页码: 3259-3266
• 关键词: games; Aggregates; CONVERGENCE; Nash equilibrium; Couplings; Distributed algorithms; Heuristic algorithms; Aggregative games; game theory; operator theory

摘要

We consider aggregative games with affine coupling constraints, where agents have partial information on the aggregate value and can only communicate with neighboring agents. We propose a single-layer distributed algorithm that reaches a variational generalized Nash equilibrium, under constant step sizes. The algorithm works on a single timescale, i.e., it does not require multiple communication rounds between agents before updating their action. The convergence proof leverages an invariance property of the aggregate estimates and relies on a forward-backward splitting for two preconditioned operators and their restricted (strong) monotonicity properties on the consensus subspace.