Distributed Nash equilibrium seeking for aggregative games with coupled constraints

TL;DR

This paper introduces a distributed continuous-time algorithm for aggregative games with coupled constraints, enabling agents to find generalized Nash equilibria using local information exchange, even with changing network topologies.

Contribution

It presents a novel distributed algorithm based on projected and non-smooth tracking dynamics, with proven convergence for time-varying interaction networks.

Findings

Algorithm converges to generalized Nash equilibrium.

Effective for time-varying network topologies.

Combines variational inequality and Lyapunov techniques.

Abstract

In this paper, we study a distributed continuous-time design for aggregative games with coupled constraints in order to seek the generalized Nash equilibrium by a group of agents via simple local information exchange. To solve the problem, we propose a distributed algorithm based on projected dynamics and non-smooth tracking dynamics, even for the case when the interaction topology of the multi-agent network is time-varying. Moreover, we prove the convergence of the non-smooth algorithm for the distributed game by taking advantage of its special structure and also combining the techniques of the variational inequality and Lyapunov function.