Convergence of Potential Mean-Field Games via Lyapunov Methods

TL;DR

This paper proves convergence of solutions in potential mean-field games on a torus using Lyapunov methods, even without monotonicity, and applies results to Kuramoto models.

Contribution

It introduces a novel Lyapunov functional for MFGs, establishes convergence without monotonicity, and provides a new uniqueness criterion for stationary equilibria.

Findings

Weak limits of time-dependent equilibria are stationary.

Convergence occurs when the stationary solution is unique.

All equilibria in the Kuramoto MFG converge to the incoherent state.

Abstract

We consider discounted infinite-horizon potential mean-field games (MFGs) on the $d$-dimensional torus. Without imposing monotonicity assumptions, we prove that every weak limit point of a time-dependent equilibrium, as time tends to infinity, is a stationary equilibrium. As a consequence, equilibria converge whenever the stationary solution is unique. The short proof is based on a novel Lyapunov functional for the time-dependent MFG system. We also provide a new uniqueness criterion for stationary equilibria. Finally, we apply our results to the subcritical Kuramoto MFG studied by Carmona, Cormier, and Soner, showing that every equilibrium converges to the incoherent solution.