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In this paper, we study proximal type dynamics in the context ofnoncooperative multi-agent network games. These dynamics arise in differentapplications, since they describe distributed decision making in multi-agentnetworks, e.g., in opinion dynamics, distributed model fitting and networkinformation fusion, where the goal of each agent is to seek an equilibriumusing local information only. We analyse several conjugations of this class ofgames, providing convergence results, or designing equilibrium seekingalgorithms when the original dynamics fail to converge. For the games subjectonly to local constraints we look into both synchronous/asynchronous dynamicsand time-varying communication networks. For games subject in addition tocoupling constraints, we design an equilibrium seeking algorithm converging toa special class of game equilibria. Finally, we validate the theoreticalresults via numerical simulations on opinion dynamics and distributed modelfitting.

Asynchronous and time-varying proximal type dynamics multi-agent network games