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This paper investigates first the existence and uniqueness of solutions for McKean-Vlasov forward-backward doubly stochastic differential equations (MV-FBDSDEs) in infinite-dimensional real separable Hilbert spaces. These equations combine…

Probability · Mathematics 2024-07-15 AbdulRahman Al-Hussein , Abdelhakim Ninouh , Boulakhras Gherbal

This paper studies social optima and Nash games for mean field linear quadratic control systems, where subsystems are coupled via dynamics and individual costs. For the social control problem, we first obtain a set of forward-backward…

Optimization and Control · Mathematics 2019-04-17 Bingchang Wang , Huanshui Zhang

This project investigates numerical methods for solving fully coupled forward-backward stochastic differential equations (FBSDEs) of McKean-Vlasov type. Having numerical solvers for such mean field FBSDEs is of interest because of the…

Mean-field backward doubly stochastic differential equations (MF-BDSDEs, for short) are introduced and studied. The existence and uniqueness of solutions for MF-BDSDEs is established. One probabilistic interpretation for the solutions to a…

Probability · Mathematics 2011-08-30 Tianxiao Wang , Qingfeng Zhu , Yufeng Shi

This paper is devoted to a global stochastic maximum principle for conditional mean-field forward-backward stochastic differential equations (FBSDEs, for short) with regime switching. The control domain is unnecessarily convex and the…

Optimization and Control · Mathematics 2022-12-06 Tao Hao , Jiaqiang Wen , Jie Xiong

We consider the value function of a stochastic optimal control of degenerate diffusion processes in a domain $D$. We study the smoothness of the value function, under the assumption of the non-degeneracy of the diffusion term along the…

Probability · Mathematics 2013-02-28 Wei Zhou

We introduce a class of backward stochastic differential equations (BSDEs) on the Wasserstein space of probability measures. This formulation extends the classical correspondence between BSDEs, stochastic control, and partial differential…

Probability · Mathematics 2025-07-01 Mao Fabrice Djete

This paper is dedicated to the presentation and the analysis of a numerical scheme for forward-backward SDEs of the McKean-Vlasov type, or equivalently for solutions to PDEs on the Wasserstein space. Because of the mean field structure of…

Probability · Mathematics 2017-03-07 Jean-François Chassagneux , Dan Crisan , François Delarue

In this paper, we consider a system of forward-backward stochastic differential equations (FBSDEs) with monotone functionals. We show the existence and uniqueness of such a system by the method of continuation similarly to Peng and Wu…

Probability · Mathematics 2018-08-07 Saran Ahuja , Weiluo Ren , Tzu-Wei Yang

We consider the stochastic optimal control problem of McKean-Vlasov stochastic differential equation where the coefficients may depend upon the joint law of the state and control. By using feedback controls, we reformulate the problem into…

Probability · Mathematics 2017-03-09 Huyên Pham , Xiaoli Wei

This paper studies a stochastic mean-field linear-quadratic Stackelberg differential game with random coefficients. The interaction between mean-field terms and random coefficients precludes the direct use of conventional decoupling…

Optimization and Control · Mathematics 2026-05-22 Ying Yang , Jie Xiong , Zhouyu Wang

In this article, from the viewpoint of control theory, we discuss the relationships among the commonly used monotonicity conditions that ensure the well-posedness of the solutions arising from problems of mean field games (MFGs) and mean…

Optimization and Control · Mathematics 2024-12-09 Alain Bensoussan , Ziyu Huang , Shanjian Tang , Sheung Chi Phillip Yam

This paper studies a class of mean-field control (MFC) problems with singular controls under general dynamic state-control-law constraints. We first propose a customized relaxed control formulation to cope with the dynamic mixed constraints…

Optimization and Control · Mathematics 2026-04-28 Lijun Bo , Jingfei Wang , Xiang Yu

We consider a mean-field control problem in which admissible controls are required to be adapted to the common noise filtration. The main objective is to show how the mean-field control problem can be approximates by time consistent…

Optimization and Control · Mathematics 2025-09-19 Bruno Bouchard , Xiaolu Tan

This paper is concerned with linear quadratic optimal control problems for mean-field backward stochastic differential equations (MF-BSDEs, for short) with deterministic coefficients. The optimality system, which is a linear mean-field…

Optimization and Control · Mathematics 2016-10-11 Xun Li , Jingrui Sun , Jie Xiong

Building on previous work on the stochastic analysis for Grassmann random variables, we introduce a forward-backward stochastic differential equation (FBSDE) which provides a stochastic quantisation of Grassmann measures. Our method is…

Probability · Mathematics 2024-06-21 Francesco C. De Vecchi , Luca Fresta , Massimiliano Gubinelli

In this paper we present a novel sampling-based numerical scheme designed to solve a certain class of stochastic optimal control problems, utilizing forward and backward stochastic differential equations (FBSDEs). By means of a nonlinear…

Systems and Control · Computer Science 2020-06-18 Ioannis Exarchos , Evangelos A. Theodorou

We a controlled system driven by a coupled forward-backward stochastic differential equation (FBSDE) with a non degenerate diffusion matrix. The cost functional is defined by the solution of the controlled backward stochastic differential…

Optimization and Control · Mathematics 2017-02-02 Khaled Bahlali , Omar Kebiri , Brahim Mezerdi , Ahmed Mtiraoui

This paper presents a further investigation of the properties of infinite-time mean field forward-backward stochastic differential equations (FBSDEs) and the associated elliptic master equations, which were introduced in [18] as…

Probability · Mathematics 2026-04-28 Yongsheng Song , Zeyu Yang

This paper is devoted to the numerical resolution of McKean-Vlasov control problems via the class of mean-field neural networks introduced in our companion paper [25] in order to learn the solution on the Wasserstein space. We propose…

Optimization and Control · Mathematics 2024-03-20 Huyên Pham , Xavier Warin