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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 propose and study the stochastic path-dependent Hamilton-Jacobi-Bellman (SPHJB) equation that arises naturally from the optimal stochastic control problem of stochastic differential equations with path-dependence and…

Probability · Mathematics 2020-06-24 Jinniao Qiu

We study an optimal control problem of McKean--Vlasov branching diffusion processes, in which the interaction term is determined by the marginal measure induced by all alive particles in the system. Accordingly, the value function is…

Optimization and Control · Mathematics 2025-12-02 Julien Claisse , Jiazhi Kang , Tianxu Lan , Xiaolu Tan

In this paper, we are concerned with the classical solvability of a class of second-order Hamilton-Jacobi-Bellman equations (HJB equations) arising from stochastic optimal control problems with linear dynamics and uniformly convex cost…

Optimization and Control · Mathematics 2025-12-19 Jinghua Li , Zhiyong Yu

A general time-inconsistent optimal control problem is considered for stochastic differential equations with deterministic coefficients. Under suitable conditions, a Hamilton-Jacobi-Bellman type equation is derived for the equilibrium value…

Optimization and Control · Mathematics 2012-04-04 Jiongmin Yong

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

This paper is devoted to the analysis of a finite horizon discrete-time stochastic optimal control problem, in presence of constraints. We study the regularity of the value function which comes from the dynamic programming algorithm. We…

Optimization and Control · Mathematics 2007-05-23 M. Papi , S. Sbaraglia

We consider a zero-sum stochastic differential controller-and-stopper game in which the state process is a controlled diffusion evolving in a multi-dimensional Euclidean space. In this game, the controller affects both the drift and the…

Optimization and Control · Mathematics 2013-01-15 Erhan Bayraktar , Yu-Jui Huang

This paper mainly investigates reflected stochastic recursive control problems governed by jump-diffusion dynamics. The system's state evolution is described by a stochastic differential equation driven by both Brownian motion and Poisson…

Optimization and Control · Mathematics 2025-05-15 Lu Liu , Qingmeng Wei

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 note, we demonstrate that a locally semiconvex viscosity supersolution to a possibly degenerate fully nonlinear elliptic Hamilton-Jacobi-Bellman (HJB) equation is differentiable along the directions spanned by the range of the…

Optimization and Control · Mathematics 2025-01-28 Salvatore Federico , Giorgio Ferrari , Mauro Rosestolato

Stochastic optimal control control problems with merely measurable coefficients are not well understood. In this manuscript, we consider fully non-linear stochastic optimal control problems in infinite horizon with measurable coefficients…

Optimization and Control · Mathematics 2026-05-21 Filippo de Feo

We study a class of backward stochastic differential equations (BSDEs) driven by a random measure or, equivalently, by a marked point process. Under appropriate assumptions we prove well-posedness and continuous dependence of the solution…

Probability · Mathematics 2012-05-24 Fulvia Confortola , Marco Fuhrman

This paper proposes two algorithms for solving stochastic control problems with deep learning, with a focus on the utility maximisation problem. The first algorithm solves Markovian problems via the Hamilton Jacobi Bellman (HJB) equation.…

Computational Finance · Quantitative Finance 2024-10-15 Ashley Davey , Harry Zheng

The Hamilton Jacobi Bellman Equation (HJB) provides the globally optimal solution to large classes of control problems. Unfortunately, this generality comes at a price, the calculation of such solutions is typically intractible for systems…

Optimization and Control · Mathematics 2014-09-23 Matanya B. Horowitz , Anil Damle , Joel W. Burdick

In this paper we study an optimization problem in which the control is information, more precisely, the control is a $\sigma$-algebra or a filtration. In a dynamic setting, we establish the dynamic programming principle and the law…

Optimization and Control · Mathematics 2026-03-31 Zihao Gu , Jianfeng Zhang

This work is devoted to the study of optimal control of stochastic functional differential equations (SFDEs) and its application to mathematical finance. By using the Dynkin formula and solution of the Dirichlet-Poisson problem, the…

Optimization and Control · Mathematics 2014-04-04 Edson A. Coayla-Teran , Anatoly Swishchuk

We study a class of zero-sum stochastic games between a stopper and a singular-controller, previously considered in [Bovo and De Angelis (2025)]. The underlying singularly-controlled dynamics takes values in…

Optimization and Control · Mathematics 2025-06-25 Andrea Bovo , Alessandro Milazzo

This paper studies a class of non$-$Markovian singular stochastic control problems, for which we provide a novel probabilistic representation. The solution of such control problem is proved to identify with the solution of a $Z-$constrained…

Optimization and Control · Mathematics 2018-02-27 Romuald Elie , Ludovic Moreau , Dylan Possamaï

This paper addresses the challenge of time-inconsistent stochastic control within a continuous-time framework. Its primary focus lies in uncovering a probabilistic representation, specifically in the shape of a system of backward stochastic…

Optimization and Control · Mathematics 2026-03-24 Dylan Possamaï , Mateo Rodriguez Polo
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