Mean-Field Stochastic Control with Elephant Memory in Finite and Infinite Time Horizon

TL;DR

This paper develops stochastic control theory for mean-field systems with elephant memory, providing existence, uniqueness, and optimality conditions for both finite and infinite horizons, with applications to linear quadratic and consumption problems.

Contribution

It introduces novel maximum principles for control of mean-field systems with elephant memory in both finite and infinite time horizons.

Findings

Established existence and uniqueness of solutions.

Derived necessary and sufficient maximum principles.

Applied results to linear quadratic and consumption problems.

Abstract

Our purpose of this paper is to study stochastic control problem for systems driven by mean-field stochastic differential equations with elephant memory, in the sense that the system (like the elephants) never forgets its history. We study both the finite horizon case and the infinite time horizon case. - In the finite horizon case, results about existence and uniqueness of solutions of such a system are given. Moreover, we prove sufficient as well as necessary stochastic maximum principles for the optimal control of such systems. We apply our results to solve a mean-field linear quadratic control problem. - For infinite horizon, we derive sufficient and necessary maximum principles. As an illustration, we solve an optimal consumption problem from a cash flow modelled by an elephant memory mean-field system.