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In this paper, we present three distributed algorithms to solve a class ofgeneralized Nash equilibrium (GNE) seeking problems in strongly monotone games.The first one (SD-GENO) is based on synchronous updates of the agents, whilethe second and the third (AD-GEED and AD-GENO) represent asynchronous solutionsthat are robust to communication delays. AD-GENO can be seen as a refinement ofAD-GEED, since it only requires node auxiliary variables, enhancing thescalability of the algorithm. Our main contribution is to prove converge to avariational GNE of the game via an operator-theoretic approach. Finally, weapply the algorithms to network Cournot games and show how different activationsequences and delays affect convergence. We also compare the proposedalgorithms to the only other in the literature (ADAGNES), and observe thatAD-GENO outperforms the alternative.

An asynchronous distributed and scalable generalized Nash equilibrium seeking algorithm for strongly monotone games