Lipschitz solutions to mean field games with a major player and applications

TL;DR

This paper develops a new weak solution concept for mean field games with a major player, proving uniqueness, existence, and an efficient algorithm under Lipschitz conditions and monotonicity assumptions.

Contribution

It introduces a Lipschitz solution framework for MFGs with a major player, extending previous notions and providing existence, uniqueness, and a convergent algorithm.

Findings

Uniqueness of sufficiently smooth solutions under Lipschitz conditions.

Existence and uniqueness of solutions for MFGs with a major player on arbitrary intervals.

An exponentially convergent algorithm for solving the system.

Abstract

This paper introduces a notion of weak solution for the coupled system of master equations in mean field games with a major player. It extends the previously introduced notion of Lipschitz solutions in mean field games. By relying on a probabilistic representation of the system of master equations, we prove that there can exist at most one sufficiently smooth solution and that it is consistent with the associated Nash equilibrium. In this approach, coefficients are only required to be Lipschitz, in particular, no differentiability assumption with respect to probability measures is needed. In a second part, we apply this notion of solution to prove the existence and uniqueness of solutions to MFGs with a major player on intervals of arbitrary length. Our argument relies on assuming that the intensity of the Brownian common noise driving the state of the major player is sufficiently large, as well as a joint displacement monotonicity assumption between the coefficients of minor players and those of the major player. Most notably, this joint monotonicity allows us to prove that the threshold of volatility can be taken independently of the horizon of the game considered, without any long time decoupling assumption on the dependence between minor players and the major player. Finally, inspired by recent extragradient methods for mean field games, we present an algorithm that converges exponentially fast to the solution of the major-minor probabilistic system under this monotonicity assumption. Thanks to the generality of our approach, all results presented in this article hold for mean field games of controls with a major player.