Distributed generalized Nash equilibrium seeking approach via surrogate functions for noncooperative nonconvex games

Abstract

This paper addresses distributed generalized Nash equilibrium seeking in noncooperative nonconvex games, where the decisions of players are subject to coupled nonconvex constraints and bound constraints. To address the limitations of existing approaches that either cannot handle bound constraints or require external augmentation terms (which incur high computational costs), a multi-agent system based on surrogate functions for nonconvex games is proposed. The convergence of the multi-agent system to a local variational generalized Nash equilibrium is proven. To demonstrate the effectiveness of the proposed multi-agent system, three numerical examples are presented to validate the main theoretical results.