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In this work we mainly prove the existence and pathwise uniqueness of solutions to general backward doubly stochastic differential equations with jumps appearing in both forward and backward integral parts. Several comparison theorems under…

Probability · Mathematics 2017-04-12 Wei Xu

This paper considers the problem of partially observed optimal control for forward stochastic systems which are driven by Brownian motions and an independent Poisson random measure with a feature that the cost functional is of mean-field…

Probability · Mathematics 2014-03-19 Yaozhong Hu , David Nualart , Qing Zhou

We establish existence and uniqueness for a wide class of Markovian systems of backward stochastic differential equations (BSDE) with quadratic nonlinearities. This class is characterized by an abstract structural assumption on the…

Probability · Mathematics 2017-03-10 Hao Xing , Gordan Žitković

In this study, we consider a class of backward SDE driven by jump Markov process. An existence and uniqueness result to this kind of equations is obtained in a locally Lipschitz case. We essentially approximate the initial problem by…

Probability · Mathematics 2018-12-27 K. Abdelhadi , N. Khelfallah

Two discretizations of a class of locally Lipschitz Markovian backward stochastic differential equations (BSDEs) are studied. The first is the classical Euler scheme which approximates a projection of the processes Z, and the second a novel…

Probability · Mathematics 2014-08-21 Plamen Turkedjiev

In this paper we look at ergodic BSDEs in the case where the forward dynamics are given by the solution to a non-autonomous (time-periodic coefficients) Ornstein-Uhlenbeck SDE with L\'evy noise, taking values in a separable Hilbert space.…

Probability · Mathematics 2015-11-11 Samuel N. Cohen , Victor Fedyashov

It is shown that non-Markovian master equations for an open system which are local in time can be unravelled through a piecewise deterministic quantum jump process in its Hilbert space. We derive a stochastic Schr\"odinger equation that…

Quantum Physics · Physics 2009-11-13 Heinz-Peter Breuer , Jyrki Piilo

In this paper, we consider a class of stochastic control problems for stochastic differential equations with random coefficients. The control domain need not to be convex but the control process is not allowed to enter in diffusion term.…

Optimization and Control · Mathematics 2020-08-06 Ishak Alia , Mohamed Sofiane Alia

This paper is concerned with a general maximum principle for the fully coupled forward-backward stochastic optimal control problem with jumps, where the control domain is not necessarily convex, within the progressively measurable…

Optimization and Control · Mathematics 2025-03-27 Bin Wang , Yu Si , Jingtao Shi

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

We study backward stochastic difference equations (BS{\Delta}E) driven by a d-dimensional stochastic process on a lattice whose increments have only d + 1 possible values that generates the lattice. Regarding the driving process as a d…

Probability · Mathematics 2026-01-14 Masaaki Fukasawa , Takashi Sato , Jun Sekine

In this paper we study stochastic optimal control problems of fully coupled forward-backward stochastic differential equations (FBSDEs). The recursive cost functionals are defined by controlled fully coupled FBSDEs. We study two cases of…

Optimization and Control · Mathematics 2013-02-06 Juan Li , Qingmeng Wei

In this paper, we consider dynamic risk measures induced by backward stochastic differential equations (BSDEs). We discuss different examples that come up in the literature, including the entropic risk measure and the risk measure arising…

Probability · Mathematics 2024-08-07 Nacira Agram , Jan Rems , Emanuela Rosazza Gianin

A backward stochastic differential equation (BSDE) is an SDE of the form $-dY_t = f(t,Y_t,Z_t)dt - Z_t^*dW_t;\ Y_T = \xi$. The subject of BSDEs has seen extensive attention since their introduction in the linear case by Bismut (1973) and in…

Probability · Mathematics 2023-12-13 Weiye Yang

Stochastic differential equations (SDEs) using jump-diffusion processes describe many natural phenomena at the microscopic level. Since they are commonly used to model economic and financial evolutions, the calibration and optimal control…

Optimization and Control · Mathematics 2025-05-08 Jan Bartsch , Alfio Borzi , Gabriele Ciaramella , Jan Reichle

In this paper, we propose a deep forward-backward stochastic differential equation (FBSDE) based control algorithm for locomotion tasks. We also include state constraints in the FBSDE formulation to impose stable walking solutions or other…

Robotics · Computer Science 2021-07-19 Bolun Dai , Virinchi Roy Surabhi , Prashanth Krishnamurthy , Farshad Khorrami

In this paper, we study a class of stochastic optimal control problem with jumps under partial information. More precisely, the controlled systems are described by a fully coupled nonlinear multi- dimensional forward-backward stochastic…

Optimization and Control · Mathematics 2009-11-18 Qingxin Meng

We consider the optimal control problem of stochastic evolution equations in a Hilbert space under a recursive utility, which is described as the solution of a backward stochastic differential equation (BSDE). A very general maximum…

Optimization and Control · Mathematics 2024-02-06 Guomin Liu , Shanjian Tang

In this paper, we focus on the stochastic representation of a system of coupled Hamilton-Jacobi-Bellman-Isaacs (HJB-Isaacs (HJBI), for short) equations which is in fact a system of coupled Isaacs' type integral-partial differential…

Optimization and Control · Mathematics 2023-07-12 Sheng Luo , Wenqiang Li , Xun Li , Qingmeng Wei

In computational system biology, the mesoscopic model of reaction-diffusion kinetics is described by a continuous time, discrete space Markov process. To simulate diffusion stochastically, the jump coefficients are obtained by a…

Numerical Analysis · Mathematics 2018-02-19 Lina Meinecke , Stefan Engblom , Andreas Hellander , Per Lötstedt