Optimal Control of the Nonlinear Stochastic Fokker--Planck Equation

TL;DR

This paper develops a comprehensive control framework for the nonlinear stochastic Fokker--Planck equation, establishing well-posedness, optimal controls, and a stochastic maximum principle, with applications to financial systems.

Contribution

It extends control theory to nonlinear stochastic Fokker--Planck equations, providing new optimality conditions and connecting to McKean--Vlasov SDEs.

Findings

Proved well-posedness and existence of optimal controls.

Formulated a stochastic maximum principle for the problem.

Applied results to financial system intervention models.

Abstract

We consider a control problem for the nonlinear stochastic Fokker--Planck equation. This equation describes the evolution of the distribution of nonlocally interacting particles affected by a common source of noise. The system is directed by a controller that acts on the drift term with the goal of minimising a cost functional. We establish the well-posedness of the state equation, prove the existence of optimal controls, and formulate a stochastic maximum principle (SMP) that provides necessary and sufficient optimality conditions for the control problem. The adjoint process arising in the SMP is characterised by a nonlocal (semi)linear backward SPDE for which we study existence and uniqueness. We also rigorously connect the control problem for the nonlinear stochastic Fokker--Planck equation to the control of the corresponding McKean--Vlasov SDE that describes the motion of a representative particle. Our work extends existing results for the control of the Fokker--Planck equation to nonlinear and stochastic dynamics. In particular, the sufficient SMP, which we obtain by exploiting the special structure of the Fokker--Planck equation, seems to be novel even in the linear deterministic setting. We illustrate our results with an application to a model of government interventions in financial systems, supplemented by numerical illustrations.