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In this paper we consider the maximum principle of optimal control for a stochastic control problem. This problem is governed by a system of fully coupled multi-dimensional forward-backward doubly stochastic differential equation with…

Optimization and Control · Mathematics 2018-09-07 AbdulRahman Al-Hussein , Boulakhras Gherbal

Backward doubly stochastic Volterra integral equations (BDSVIEs, for short) are introduced and studied systematically. Well-posedness of BDSVIEs in the sense of introduced M-solutions is established. A comparison theorem for BDSVIEs is…

Probability · Mathematics 2019-06-26 Yufeng Shi , Jiaqiang Wen , Jie Xiong

This paper formulates and studies a stochastic maximum principle for forward-backward stochastic Volterra integral equations (FBSVIEs in short), while the control area is assumed to be convex. Then a linear quadratic (LQ in short) problem…

Probability · Mathematics 2010-04-14 Tianxiao Wang , Yufeng Shi

In this paper, we prove the necessary and sufficient maximum principles (NSMPs in short) for the optimal control of systems described by a quasilinear stochastic heat equation within convex control domains, which all the coefficients…

Optimization and Control · Mathematics 2012-11-01 Liangquan Zhang , Yufeng Shi

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 propose a new methodology for state constrained stochastic optimal control (SOC) problems. The solution is based on past work in solving SOC problems using forward-backward stochastic differential equations (FBSDE). Our…

Systems and Control · Electrical Eng. & Systems 2021-04-07 Bolun Dai , Prashanth Krishnamurthy , Andrew Papanicolaou , Farshad Khorrami

We are concerned with high-dimensional coupled FBSDE systems approximated by the deep BSDE method of Han et al. (2018). It was shown by Han and Long (2020) that the errors induced by the deep BSDE method admit a posteriori estimate…

Numerical Analysis · Mathematics 2025-01-22 Balint Negyesi , Zhipeng Huang , Cornelis W. Oosterlee

Recently, the deep learning method has been used for solving forward-backward stochastic differential equations (FBSDEs) and parabolic partial differential equations (PDEs). It has good accuracy and performance for high-dimensional…

Numerical Analysis · Mathematics 2020-02-04 Shaolin Ji , Shige Peng , Ying Peng , Xichuan Zhang

In this paper, we investigate the Markovian iteration method for solving coupled forward-backward stochastic differential equations (FBSDEs) featuring a fully coupled forward drift, meaning the drift term explicitly depends on both the…

Numerical Analysis · Mathematics 2025-04-04 Zhipeng Huang , Cornelis W. Oosterlee

In this paper we study useful estimates, in particular $L^p$-estimates, for fully coupled forward-backward stochastic differential equations (FBSDEs) with jumps. These estimates are proved at one hand for fully coupled FBSDEs with jumps…

Probability · Mathematics 2013-02-06 Juan Li , Qingmeng Wei

In this work, we concern with the high order numerical methods for coupled forward-backward stochastic differential equations (FBSDEs). Based on the FBSDEs theory, we derive two reference ordinary differential equations (ODEs) from the…

Numerical Analysis · Mathematics 2014-03-27 Weidong Zhao , Yu Fu , Tao Zhou

We study optimal stochastic control problems of general coupled systems of forward-backward stochastic differential equations with jumps. By means of the It\^o-Ventzell formula the system is transformed to a controlled backward stochastic…

Optimization and Control · Mathematics 2017-01-12 Bernt Øksendal , Agnès Sulem , Tusheng Zhang

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

This paper investigates a class of unified stochastic linear quadratic Gaussian (LQG) social optima problems involving a large number of weakly-coupled interactive agents under a {generalized} setting. For each individual agent, the control…

Optimization and Control · Mathematics 2020-05-15 Zhenghong Qiu , Jianhui Huang , Tinghan Xie

This paper is concerned with a Stackelberg stochastic differential game, where the systems are driven by stochastic differential equation (SDE for short), in which the control enters the randomly disturbed coefficients (drift and…

Optimization and Control · Mathematics 2021-08-12 Liangquan Zhang , Wei Zhang

This is one of our series papers on multistep schemes for solving forward backward stochastic differential equations (FBSDEs) and related problems. Here we extend (with non-trivial updates) our multistep schemes in [W. Zhao, Y. Fu and T.…

Numerical Analysis · Mathematics 2015-02-12 Kong Tao , Weidong Zhao , Tao Zhou

This paper addresses a class of two-person zero-sum stochastic differential equations, which encompass Markov chains and fractional Brownian motion, and satisfy some monotonicity conditions over an infinite time horizon. Within the…

Optimization and Control · Mathematics 2024-12-24 Chang Liu , Hongtao Fan , Yajing Li

This paper studies the optimal control problems of stochastic evolution equations with infinite delay of general functional type. By introducing a non-anticipative path derivative and its infinite-window dual operator, we derive the…

Optimization and Control · Mathematics 2026-05-26 Guanwei Cheng

We study a coupled system of controlled stochastic differential equations (SDEs) driven by a Brownian motion and a compensated Poisson random measure, consisting of a forward SDE in the unknown process $X(t)$ and a \emph{predictive…

Optimization and Control · Mathematics 2015-05-20 Bernt Øksendal , Agnès Sulem

This paper introduces a new formulation for stochastic optimal control and stochastic dynamic optimization that ensures safety with respect to state and control constraints. The proposed methodology brings together concepts such as…

Systems and Control · Electrical Eng. & Systems 2021-02-19 Marcus Aloysius Pereira , Ziyi Wang , Ioannis Exarchos , Evangelos A. Theodorou