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This paper establishes a stochastic maximum principle for optimal control problems governed by time-changed forward-backward stochastic differential equations with L\'evy noise. The system incorporates a random, non-decreasing operational…

Optimization and Control · Mathematics 2026-03-27 Jingwei Chen , Jun Ye , Feng Chen

This work investigates the optimal control problem for reflected McKean-Vlasov SDEs and the viscosity solutions to Hamilton-Jacobi-Bellman(HJB) equations on the Wasserstein space in terms of intrinsic derivative. It follows from the flow…

Probability · Mathematics 2023-09-18 Jinghai Shao

We show that the value function of a stochastic control problem is the unique solution of the associated Hamilton-Jacobi-Bellman (HJB) equation, completely avoiding the proof of the so-called dynamic programming principle (DPP). Using…

Probability · Mathematics 2013-09-25 Erhan Bayraktar , Mihai Sirbu

We consider an optimal control problem for piecewise deterministic Markov processes (PDMPs) on a bounded state space. The control problem under study is very general: a pair of controls acts continuously on the deterministic flow and on the…

Optimization and Control · Mathematics 2018-02-14 Elena Bandini

The analysis of dynamical systems is a fundamental tool in the natural sciences and engineering. It is used to understand the evolution of systems as large as entire galaxies and as small as individual molecules. With predefined conditions…

Machine Learning · Statistics 2024-12-19 Ludwig Winkler

We consider a classical finite horizon optimal control problem for continuous-time pure jump Markov processes described by means of a rate transition measure depending on a control parameter and controlled by a feedback law. For this class…

Probability · Mathematics 2015-01-20 Elena Bandini , Marco Fuhrman

The present paper considers a stochastic optimal control problem, in which the cost function is defined through a backward stochastic differential equation with infinite horizon driven by G-Brownian motion. Then we study the regularities of…

Probability · Mathematics 2017-06-13 Mingshang Hu , Falei Wang

Model predictive control solves a constrained optimization problem online in order to compute an implicit closed-loop control policy. Recursive feasibility -- guaranteeing that the optimal control problem will have a solution at every time…

Optimization and Control · Mathematics 2024-10-16 Jacob W. Knaup , Panagiotis Tsiotras

We study a class of reflected backward stochastic differential equations with nonpositive jumps and upper barrier. Existence and uniqueness of a minimal solution is proved by a double penalization approach under regularity assumptions on…

Probability · Mathematics 2013-08-27 Sébastien Choukroun , Andrea Cosso , Huyen Pham

In this article, we consider a receding horizon control of discrete-time state-dependent jump linear systems, particular kind of stochastic switching systems, subject to possibly unbounded random disturbances and probabilistic state…

Systems and Control · Computer Science 2014-07-25 Shaikshavali Chitraganti , Samir Aberkane , Christophe Aubrun , Guillermo Valencia-Palomo , Vasile Dragan

We consider a reflected backward stochastic differential equations with default time and an optional barrier in a filtration generated by a one-dimensional Brownian motion and a defaultable process. We suppose that the barrier have…

Probability · Mathematics 2026-05-07 Badr Elmansouri , Mohamed El Otmani

We prove convergence of the proximal policy gradient method for a class of constrained stochastic control problems with control in both the drift and diffusion of the state process. The problem requires either the running or terminal cost…

Optimization and Control · Mathematics 2025-05-27 Ashley Davey , Harry Zheng

We consider a stochastic control problem which is composed of a controlled stochastic differential equation, and whose associated cost functional is defined through a controlled backward stochastic differential equation. Under appropriate…

Probability · Mathematics 2009-02-17 Rainer Buckdahn , Boubakeur Labed , Catherine Rainer , Lazhar Tamer

We address a class of backward stochastic differential equations on a bounded interval, where the driving noise is a marked, or multivariate, point process. Assuming that the jump times are totally inaccessible and a technical condition…

Probability · Mathematics 2016-06-28 Fulvia Confortola , Marco Fuhrman , Jean Jacod

Optimal control of interacting particles governed by stochastic evolution equations in Hilbert spaces is an open area of research. Such systems naturally arise in formulations where each particle is modeled by stochastic partial…

Probability · Mathematics 2025-11-27 Filippo de Feo , Fausto Gozzi , Andrzej Święch , Lukas Wessels

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

We consider a stochastic optimal control problem governed by a stochastic differential equation with delay in the control. Using a result of existence and uniqueness of a sufficiently regular mild solution of the associated…

Probability · Mathematics 2021-03-22 F. Gozzi , F. Masiero

This paper is concerned with one kind of partially observed progressive optimal control problems of coupled forward-backward stochastic systems driven by both Brownian motion and Poisson random measure with risk-sensitive criteria. The…

Optimization and Control · Mathematics 2025-04-08 Jingtao Lin , Jingtao Shi

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

We consider controller-stopper problems in which the controlled processes can have jumps. The global filtration is represented by the Brownian filtration, enlarged by the filtration generated by the jump process. We assume that there exists…

Probability · Mathematics 2013-11-20 Erhan Bayraktar , Zhou Zhou
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