Maximum principle for optimal control of stochastic evolution equations with recursive utilities

TL;DR

This paper develops a very general maximum principle for optimal control of stochastic evolution equations with recursive utilities, accommodating non-convex control domains and variable generator functions.

Contribution

It introduces a novel maximum principle for stochastic evolution equations with recursive utilities, including a unique second-order adjoint process characterized by an operator-valued backward stochastic integral equation.

Findings

Maximum principle applicable to non-convex control domains.

Characterization of the second-order adjoint process.

Extension to generators depending on the second unknown variable.

Abstract

We consider the optimal control problem of stochastic evolution equations in a Hilbert space under a recursive utility, which is described as the solution of a backward stochastic differential equation (BSDE). A very general maximum principle is given for the optimal control, allowing the control domain not to be convex and the generator of the BSDE to vary with the second unknown variable $z$. The associated second-order adjoint process is characterized as a unique solution of a conditionally expected operator-valued backward stochastic integral equation.