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This paper is concerned with the partial information optimal control problem of wa controlled forward-backward stochastic differential equation of jump diffusion with correlated noises between the system and the observation. For this type…

Probability · Mathematics 2017-08-28 Qingxin Meng

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

We study a stochastic control problem for nonlinear systems governed by stochastic differential equations with irregular drift. The drift coefficient is assumed to decompose as $b(t,x,a)=b_1(t,x)+b_2(x)b_3(t,a)$, where $b_1$ is bounded and…

Optimization and Control · Mathematics 2026-04-02 Antoine Marie Bogso , Rhoss Likibi Pellat , Wilfried Kuissi Kamdem , Olivier Menoukeu Pamen

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. Some of the economic and financial optimization…

Optimization and Control · Mathematics 2015-09-01 Mingshang Hu , Shaolin Ji

This paper investigates a multidimensional non-homogeneous stochastic linear-quadratic optimal control problem featuring random coefficients and a terminal mean-field term in the cost functional, enabling its direct application to…

Optimization and Control · Mathematics 2026-05-27 Guojiang Shao , Zuo Quan Xu , Qi Zhang

This paper analyzes a discretization of a stochastic parabolic optimal control problem, where the diffusion term contains the control variable. With rough data, the convergence of the discretization is derived. In addition, a Monte-Carlo…

Numerical Analysis · Mathematics 2022-08-31 Binjie Li , Qin Zhou , Xiaoping Xie

The optimal control problem of stochastic systems is commonly solved via robust or scenario-based optimization methods, which are both challenging to scale to long optimization horizons. We cast the optimal control problem of a stochastic…

Machine Learning · Computer Science 2025-09-17 Etienne Buehrle , Christoph Stiller

The purpose of this paper is to derive some pointwise second-order necessary conditions for stochastic optimal controls in the general case that the control variable enters into both the drift and the diffusion terms. When the control…

Optimization and Control · Mathematics 2014-05-29 Haisen Zhang , Xu Zhang

We study a class of controlled rough differential equations. It is shown that the value function satisfies a HJB type equation; we also establish a form of the Pontryagin maximum principle. Deterministic problems of this type arise in the…

Probability · Mathematics 2013-05-21 Joscha Diehl , Peter Friz , Paul Gassiat

This paper is devoted to an optimal control problem of fully coupled forward-backward stochastic differential equations driven by sub-diffusion, whose solutions are not Markov processes. The stochastic maximum principle is obtained, where…

Optimization and Control · Mathematics 2025-03-11 Chenhui Hao , Jingtao Shi , Shuaiqi Zhang

This paper provides necessary conditions of optimality for optimal control problems with time delays in both state and control variables. Different versions of the necessary conditions cover fixed end-time problems and, under additional…

Dynamical Systems · Mathematics 2017-01-09 Andrea Boccia , Richard B. Vinter

Quantum optimal control is a set of methods for designing time-varying electromagnetic fields to perform operations in quantum technologies. This tutorial paper introduces the basic elements of this theory based on the Pontryagin maximum…

Quantum Physics · Physics 2024-06-17 Q. Ansel , E. Dionis , F. Arrouas , B. Peaudecerf , S. Guérin , D. Guéry-Odelin , D. Sugny

In this study, we consider an optimal control problem driven by a stochastic differential system with a stopping time terminal cost functional. We establish the stochastic maximum principle for this new kind of an optimal control problem by…

Optimization and Control · Mathematics 2018-12-11 Shuzhen Yang

In this paper, we generalise Pontryagin's stochastic maximum principle to controlled McKean-Vlasov equations with anticipating law. The associated new type of delayed backward equations with implicit terminal condition is studied.

Optimization and Control · Mathematics 2017-07-03 Nacira Agram

For a class of Bellman equations in bounded domains we prove that sub- and supersolutions whose growth at the boundary is suitably controlled must be constant. The ellipticity of the operator is assumed to degenerate at the boundary and a…

Analysis of PDEs · Mathematics 2015-05-07 Martino Bardi , Annalisa Cesaroni , Luca Rossi

This paper investigates the robustness of stochastic optimal control for controlled regime switching diffusions. We consider systems driven by both continuous fluctuations and discrete regime changes, allowing for model misspecification in…

Optimization and Control · Mathematics 2025-11-24 Somnath Pradhan , Dinesh Rathia

In this paper, we consider optimal control problems derived by stochastic systems with delay, where control domains are non-convex and the diffusion coefficients depend on control variables. By an estimate of the integral of…

Optimization and Control · Mathematics 2022-10-25 Qixia Zhang

In this paper, the stochastic verification theorems for stochastic control problems of reflected forward-backward stochastic differential equations are studied. We carry out the work within the frameworks of classical and viscosity…

Optimization and Control · Mathematics 2023-06-07 Lu Liu , Xinlei Hu , Qingmeng Wei

This paper studies the optimization of observation channels (stochastic kernels) in partially observed stochastic control problems. In particular, existence and continuity properties are investigated mostly (but not exclusively)…

Optimization and Control · Mathematics 2012-02-09 Serdar Yüksel , Tamás Linder

In this article, the sufficient Pontryagin's maximum principle for infinite horizon discounted stochastic control problem is established. The sufficiency is ensured by an additional assumption of concavity of the Hamiltonian function.…

Optimization and Control · Mathematics 2013-03-14 Bohdan Maslowski , Petr Veverka