A stochastic maximum principle for backward delayed system via advanced stochastic differential equation (ASDE)

TL;DR

This paper develops a stochastic maximum principle for backward delayed systems using advanced stochastic differential equations (ASDEs), introduces new ASDE theory, and applies these to dynamic optimization problems with explicit solutions.

Contribution

It introduces a novel class of ASDEs for stochastic control, derives maximum principles with and without control delay, and provides explicit solutions for optimization problems.

Findings

Derived stochastic maximum principles for delayed control systems.

Established existence and uniqueness results for ASDEs.

Provided explicit solutions for optimization problems using AODEs.

Abstract

The main contributions of this paper are three fold. First, our primary concern is to investigate a class of stochastic recursive delayed control problems which arise naturally with sound backgrounds but have not been well-studied yet. For illustration purpose, some concrete examples are also provided here. We derive the stochastic maximum principle of sufficient condition to the optimal control in both cases with and without control delay. Second, it is interesting that a new class of time-advanced stochastic differential equations (ASDEs) is introduced as the adjoint process via duality relation. To our best knowledge, such equations have never been discussed in literature although they possess more academic values besides the control study here. Some existence and uniqueness result to ASDEs is presented. Third, to illustrate our theoretical results, some dynamic optimization problems are discussed based on our stochastic maximum principles. In particular, the optimal controls are derived explicitly by solving the associated time-advanced ordinary differential equation (AODE), the counterpart of the ASDE in its deterministic setup.