2019/08/31 by Dian Gadjov, Lacra Pavel
Computer Science · Decision Sciences · Mathematics · #Affine transformation #Aggregate (composite) #Constant (computer programming) #Convergence (economics) #Distributed Control Multi-Agent Systems #Game Theory and Applications #Monotonic function #Nash equilibrium #Operator (biology) #Optimization and Variational Analysis #Property (philosophy) #math.OC
paper · pdf · doi:10.1109/tac.2020.3015354
published as IEEE Transactions on Automatic Control, 2020 · 8 pages, 8 figures, submitted to TAC
openalex created_date 2019/08/13 · arxiv created 2020/08/04 · openalex publication_date 2020/08/10 · arxiv updated 2020/08/14 · openalex updated_date 2026/08/05
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.