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In this paper, we study a stochastic recursive optimal control problem in which the value functional is defined by the solution of a backward stochastic differential equation (BSDE) under $\tilde{G}$-expectation. Under standard assumptions,…

Optimization and Control · Mathematics 2021-06-08 Mingshang Hu , Shaolin Ji , Xiaojuan Li

In this paper we investigate a kind of optimal control problem of coupled forward-backward stochastic system with jumps whose cost functional is defined through a coupled forward-backward stochastic differential equation with Brownian…

Probability · Mathematics 2020-09-15 Qian Lin

This paper deals with a nonsmooth version of the connection between the maximum principle and dynamic programming principle, for the stochastic recursive control problem when the control domain is convex. By employing the notions of sub-…

Optimization and Control · Mathematics 2016-03-09 Tianyang Nie , Jingtao Shi , Zhen Wu

We study the optimal control of general stochastic McKean-Vlasov equation. Such problem is motivated originally from the asymptotic formulation of cooperative equilibrium for a large population of particles (players) in mean-field…

Probability · Mathematics 2017-01-06 Huyên Pham , Xiaoli Wei

In this paper we present a general framework that allows one to study discretization of certain dynamical systems. This generalizes earlier work on discretization of Lagrangian and Hamiltonian systems on tangent bundles and cotangent…

Dynamical Systems · Mathematics 2007-05-23 Vincent M. Guibout , Anthony M. Bloch

In this paper, we study a stochastic recursive optimal control problem in which the cost functional is described by the solution of a backward stochastic differential equation driven by G-Brownian motion. Under standard assumptions, we…

Optimization and Control · Mathematics 2014-10-15 Mingshang Hu , Shaolin Ji

This paper is concerned with the stochastic recursive optimal control problem with mixed delay. The connection between Pontryagin's maximum principle and Bellman's dynamic programming principle is discussed. Without containing any…

Optimization and Control · Mathematics 2019-12-24 Weijun Meng , Jingtao Shi

This paper is concerned with finite-level quantum memory systems for retaining initial dynamic variables in the presence of external quantum noise. The system variables have an algebraic structure, similar to that of the Pauli matrices, and…

Optimization and Control · Mathematics 2026-04-01 Igor G. Vladimirov , Ian R. Petersen , Guodong Shi

We study a stochastic control problem on a bounded domain, which arises from a continuous-time optimal management model. Via the corresponding Hamilton-Jacobi-Bellman equation the value function is shown to be jointly continuous and to…

Probability · Mathematics 2017-10-24 Ruoting Gong , Christian Houdré

In this note, we study a class of indefinite stochastic McKean-Vlasov linear-quadratic (LQ in short) control problem under the control taking nonnegative values. In contrast to the conventional issue, both the classical dynamic programming…

Optimization and Control · Mathematics 2023-10-05 Xun Li , Liangquan Zhang

In this paper, a stochastic optimal control problem is investigated in which the system is governed by a stochastic functional differential equation. In the framework of functional It\^o calculus, we build the dynamic programming principle…

Optimization and Control · Mathematics 2013-01-03 Shaolin Ji , Shuzhen Yang

This paper is concerned with a stochastic recursive optimal control problem with time delay, where the controlled system is described by a stochastic differential delayed equation (SDDE) and the cost functional is formulated as the solution…

Optimization and Control · Mathematics 2014-08-26 Jingtao Shi , Huanshui Zhang

In this paper, we study a stochastic recursive optimal control problem in which the objective functional is described by the solution of a backward stochastic differential equation driven by G-Brownian motion. Under standard assumptions, we…

Optimization and Control · Mathematics 2013-06-07 Mingshang Hu , Shaolin Ji , Shuzhen Yang

In this paper, we introduce a model-based deep-learning approach to solve finite-horizon continuous-time stochastic control problems with jumps. We iteratively train two neural networks: one to represent the optimal policy and the other to…

Machine Learning · Computer Science 2026-01-16 Patrick Cheridito , Jean-Loup Dupret , Donatien Hainaut

We study the properties of the value function associated with an optimal control problem with uncertainties, known as average or Riemann-Stieltjes problem. Uncertainties are assumed to belong to a compact metric probability space, and…

Optimization and Control · Mathematics 2024-07-19 M. Soledad Aronna , Michele Palladino , Oscar Sierra

We obtain the variational equations for backward stochastic differential equations in recursive stochastic optimal control problems, and then get the maximum principle which is novel. The control domain need not be convex, and the generator…

Optimization and Control · Mathematics 2015-07-14 Mingshang Hu

We explore the approximation of feedback control of integro-differential equations containing a fractional Laplacian term. To obtain feedback control for the state variable of this nonlocal equation we use the Hamilton--Jacobi--Bellman…

Optimization and Control · Mathematics 2022-10-19 Alessandro Alla , Marta D'Elia , Christian Glusa , Hugo Oliveira

In this paper we consider the maximum principle of optimal control for a stochastic control problem. This problem is governed by a system of fully coupled multi-dimensional forward-backward doubly stochastic differential equation with…

Optimization and Control · Mathematics 2018-09-07 AbdulRahman Al-Hussein , Boulakhras Gherbal

In this paper, we study a time-inconsistent stochastic optimal control problem with a recursive cost functional by a multi-person hierarchical differential game approach. An equilibrium strategy of this problem is constructed and a…

Optimization and Control · Mathematics 2016-06-13 Qingmeng Wei , Jiongmin Yong , Zhiyong Yu

In this paper, we consider a stochastic recursive optimal control problem under model uncertainty. In this framework, the cost function is described by solutions of a family of backward stochastic differential equations. With the help of…

Probability · Mathematics 2020-04-16 Mingshang Hu , Falei Wang