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The maximum principle for optimal control problems of fully coupled forward-backward doubly stochastic differential equations (FBDSDEs in short) in the global form is obtained, under the assumptions that the diffusion coefficients do not…

Optimization and Control · Mathematics 2012-05-28 Liangquan Zhang , Yufeng Shi

We consider a stochastic control problem for a class of nonlinear kernels. More precisely, our problem of interest consists in the optimisation, over a set of possibly non-dominated probability measures, of solutions of backward stochastic…

Probability · Mathematics 2017-07-28 Dylan Possamaï , Xiaolu Tan , Chao Zhou

This paper deals with an optimal position management problem for a market maker who has to face uncertain customer order flows in an illiquid market, where the market maker's continuous trading incurs a stochastic linear price impact.…

Pricing of Securities · Quantitative Finance 2015-09-08 Masaaki Fujii

In this paper, we investigate the controlled system described by forward-backward stochastic differential equations with the control contained in drift, diffusion and generator of BSDE. A new verification theorem is derived within the…

Optimization and Control · Mathematics 2012-05-28 Liangquan Zhang

This paper is mainly concerned with the solutions to both forward and backward mean-field stochastic partial differential equation and the corresponding optimal control problem for mean-field stochastic partial differential equation. We…

Optimization and Control · Mathematics 2016-10-11 Maoning Tang , Qingxin Meng

Stochastic optimal control problems governed by delay equations with delay in the control are usually more difficult to study than the the ones when the delay appears only in the state. This is particularly true when we look at the…

Probability · Mathematics 2015-06-22 Fausto Gozzi , Federica Masiero

In this paper, we consider a stochastic decision problem for a system governed by a stochastic differential equation, in which an optimal decision is made in such a way to minimize a vector-valued accumulated cost over a finite-time horizon…

Optimization and Control · Mathematics 2018-01-08 Getachew K. Befekadu

We study a stochastic optimal control problem for fully coupled forward-backward stochastic control systems with a nonempty control domain. For our problem, the first-order and second-order variational equations are fully coupled linear…

Optimization and Control · Mathematics 2018-12-05 Mingshang Hu , Shaolin Ji , Xiaole Xue

We are interested in stochastic control problems coming from mathematical finance and, in particular, related to model uncertainty, where the uncertainty affects both volatility and intensity. This kind of stochastic control problems is…

Probability · Mathematics 2014-05-15 Sébastien Choukroun , Andrea Cosso

The path-integral control, which stems from the stochastic Hamilton-Jacobi-Bellman equation, is one of the methods to control stochastic nonlinear systems. This paper gives a new insight into nonlinear stochastic optimal control problems…

Optimization and Control · Mathematics 2021-09-14 Jun Ohkubo

In this paper, we introduce a new type of backward stochastic differential equations (BSDEs) with infinite anticipation, where the generator depends on the entire future values of the solution in infinite horizon. We show that the new BSDEs…

Probability · Mathematics 2025-11-20 Guanwei Cheng , Shuzhen Yang

In this paper, we first establish the dynamic programming principle for stochastic optimal control problems defined on compact Riemannian manifolds without boundary. Subsequently, we derive the associated Hamilton-Jacobi-Bellman (HJB)…

Optimization and Control · Mathematics 2025-07-03 Dingqian Gao , Qi Lü

In this paper we study zero-sum two-player stochastic differential games with the help of theory of Backward Stochastic Differential Equations (BSDEs). At the one hand we generalize the results of the pioneer work of Fleming and Souganidis…

Probability · Mathematics 2011-02-19 Rainer Buckdahn , Juan Li

This paper considers optimal control of dynamical systems which are represented by nonlinear stochastic differential equations. It is well-known that the optimal control policy for this problem can be obtained as a function of a value…

Robotics · Computer Science 2014-05-30 Oktay Arslan , Evangelos Theodorou , Panagiotis Tsiotras

We develop a computationally efficient learning-based forward-backward stochastic differential equations (FBSDE) controller for both continuous and hybrid dynamical (HD) systems subject to stochastic noise and state constraints. Solutions…

Systems and Control · Electrical Eng. & Systems 2023-05-12 Bolun Dai , Prashanth Krishnamurthy , Andrew Papanicolaou , Farshad Khorrami

The aim of this work is to develop a deep learning method for solving high-dimensional stochastic control problems based on the Hamilton--Jacobi--Bellman (HJB) equation and physics-informed learning. Our approach is to parameterize the…

Optimization and Control · Mathematics 2025-06-23 Zhe Jiao , Wantao Jia , Weiqiu Zhu

In this paper, we aim to develop the theory of optimal stochastic control for branching diffusion processes where both the movement and the reproduction of the particles depend on the control. More precisely, we study the problem of…

Probability · Mathematics 2016-09-19 Julien Claisse

We introduce and study a new class of optimal switching problems, namely switching problem with controlled randomisation, where some extra-randomness impacts the choice of switching modes and associated costs. We show that the optimal value…

Probability · Mathematics 2020-01-31 Cyril Bénézet , Jean-François Chassagneux , Adrien Richou

We consider some certain nonlinear perturbations of the stochastic linear-quadratic optimization problems and study the connections between their solutions and the corresponding Markovian backward stochastic diferential equations (BSDEs).…

Optimization and Control · Mathematics 2013-01-01 Coskun Cetin

In this paper, we study the maximum principle for stochastic optimal control problems of forward-backward stochastic difference systems (FBS{\Delta}Ss) where the uncertainty is modeled by a discrete time, finite state process, rather than…

Optimization and Control · Mathematics 2019-07-10 Shailin Ji , Haodong Liu
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