Mean Field Games with Common Noises and Conditional Distribution Dependent FBSDEs

TL;DR

This paper studies mean field games with common noise and distribution-dependent coefficients, establishing existence and uniqueness of solutions to associated FBSDEs under certain conditions using novel analytical methods.

Contribution

It introduces new methods to prove existence and uniqueness of conditional distribution dependent FBSDEs in mean field games with common noise.

Findings

Existence and uniqueness of solutions under small dependence or large convexity.

Application of continuation method and fixed point theorem to FBSDEs.

Extension of methods to mean field games with common noise.

Abstract

In this paper, we consider the mean field game with a common noise and allow the state coefficients to vary with the conditional distribution in a nonlinear way. We assume that the cost function satisfies a convexity and a weak monotonicity property. We use the sufficient Pontryagin principle for optimality to transform the mean field control problem into existence and uniqueness of solution of conditional distribution dependent forward-backward stochastic differential equation (FBSDE). We prove the existence and uniqueness of solution of the conditional distribution dependent FBSDE when the dependence of the state on the conditional distribution is sufficiently small, or when the convexity parameter of the running cost on the control is sufficiently large. Two different methods are developed. The first method is based on a continuation of the coefficients, which is developed for FBSDE by Hu and Peng \cite{YH2}. We apply the method to conditional distribution dependent FBSDE. The second method is to show the existence result on a small time interval by Banach fixed point theorem and then extend the local solution to the whole time interval.