A Distributed GNE Seeking Algorithm Using the Douglas-Rachford Splitting Method

TL;DR

This paper introduces a distributed algorithm based on Douglas-Rachford splitting to find generalized Nash equilibria in networked games, requiring milder conditions and proven convergence.

Contribution

It develops a novel distributed GNE seeking algorithm using Douglas-Rachford splitting, with convergence guarantees under less restrictive assumptions.

Findings

Algorithm converges to an exact GNE under certain conditions

Requires milder assumptions than existing methods

Validated through a Nash-Cournot game example

Abstract

We consider a generalized Nash equilibrium problem (GNEP) for a network of players. Each player tries to minimize a local objective function subject to some resource constraints where both the objective functions and the resource constraints depend on other players' decisions. By conducting equivalent transformations on the local optimization problems and introducing network Lagrangian, we recast the GNEP into an operator zero-finding problem. An algorithm is proposed based on the Douglas-Rachford method to distributedly find a solution. The proposed algorithm requires milder conditions compared to the existing methods. We prove the convergence of the proposed algorithm to an exact variational generalized Nash equilibrium under two different sets of assumptions. Our algorithm is validated numerically through the example of a Nash-Cournot production game.