In this article, we study proximal type dynamics in the context of multiagent network games. We analyze several conjugations of this class of games, providing convergence results. Specifically, we look into synchronous/asynchronous dynamics with time-invariant communication network and synchronous dynamics with time-varying communication networks. Finally, we validate the theoretical results via numerical simulations on opinion dynamics. @en

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.@en