Two-person zero-sum stochastic linear quadratic control problems with Markov chains and fractional Brownian motion in infinite horizon

TL;DR

This paper develops a theoretical framework for two-player zero-sum stochastic control problems involving Markov chains and fractional Brownian motion over an infinite horizon, establishing existence, uniqueness, and optimal strategies.

Contribution

It extends Itô's formula to complex stochastic systems and applies fixed-point and approximation methods to solve infinite horizon FBSDEs in a novel zero-sum game context.

Findings

Existence and uniqueness of solutions for the FBSDEs system.

Derivation of optimal control strategies for both players.

Analysis of the impact of the cross-term in the cost function.

Abstract

This paper addresses a class of two-person zero-sum stochastic differential equations, which encompass Markov chains and fractional Brownian motion, and satisfy some monotonicity conditions over an infinite time horizon. Within the framework of forward-backward stochastic differential equations (FBSDEs) that describe system evolution, we extend the classical It$\rm\hat{o}$'s formula to accommodate complex scenarios involving Brownian motion, fractional Brownian motion, and Markov chains simultaneously. By applying the Banach fixed-point theorem and approximation methods respectively, we theoretically guarantee the existence and uniqueness of solutions for FBSDEs in infinite horizon. Furthermore, we apply the method for the first time to the optimal control problem in a two-player zero-sum game, deriving the optimal control strategies for both players by solving the FBSDEs system. Finally, we conduct an analysis of the impact of the cross-term $S(\cdot)$ in the cost function on the solution, revealing its crucial role in the optimization process.