2018/11/11 by Carlo Cenedese, Yu Kawano, Cenedese, Carlo +5
Computer Science · Decision Sciences · Medicine · #Computer Science and Game Theory (cs.GT) #Distributed Control Multi-Agent Systems #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Game Theory and Applications #Mathematical and Theoretical Epidemiology and Ecology Models #Optimization and Control (math.OC) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1811.04391
openalex publication_date 2018/11/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Distributed decision making in multi-agent networks has recently attracted significant research attention thanks to its wide applicability, e.g. in the management and optimization of computer networks, power systems, robotic teams, sensor networks and consumer markets. Distributed decision-making problems can be modeled as inter-dependent optimization problems, i.e., multi-agent game-equilibrium seeking problems, where noncooperative agents seek an equilibrium by communicating over a network. To achieve a network equilibrium, the agents may decide to update their decision variables via proximal dynamics, driven by the decision variables of the neighboring agents. In this paper, we provide an operator-theoretic characterization of convergence with a time-invariant communication network. For the time-varying case, we consider adjacency matrices that may switch subject to a dwell time. We illustrate our investigations using a distributed robotic exploration example.