The mean-field control problem for heterogeneous forward-backward systems

TL;DR

This paper addresses mean-field control problems involving complex forward-backward stochastic differential equations with heterogeneous interactions, introducing a new reduction method and deriving optimality conditions.

Contribution

It presents a novel approach to analyze well-posedness of heterogeneous mean-field FBSDEs and establishes a stochastic maximum principle for the control problem.

Findings

Reduction of complex systems to single randomized mean-field FBSDEs

Existence and uniqueness under smallness conditions

Necessary and sufficient optimality conditions via maximum principle

Abstract

We study the problem of mean-field control when the state dynamics are given by general systems of forward-backward stochastic differential equations (FBSDEs) with heterogeneous mean-field interactions. Firstly, we introduce a novel methodology for reducing the well-posedness of such systems to that of a single randomized mean-field FBSDE. As a consequence, we show that, in the fully coupled case, smallness conditions yield existence and uniqueness for both the system itself and the associated variational and adjoint systems. Secondly, we derive a stochastic maximum principle and a verification for the mean-field control problem. This provides necessary and sufficient conditions for optimality.