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math.OC2022
A deep learning method for solving stochastic optimal control problems driven by fully-coupled FBSDEs
Shaolin Ji, Shige Peng, Ying Peng +1
In this paper,we mainly focus on the numerical solution of high-dimensional stochastic optimal control problem driven by fully-coupled forward-backward stochastic differential equa…
math.OC2021★ 1 cited
A novel control method for solving high-dimensional Hamiltonian systems through deep neural networks
Shaolin Ji, Shige Peng, Ying Peng +1
In this paper, we mainly focus on solving high-dimensional stochastic Hamiltonian systems with boundary condition, which is essentially a Forward Backward Stochastic Differential E…
math.OC2020
Solving stochastic optimal control problem via stochastic maximum principle with deep learning method
Shaolin Ji, Shige Peng, Ying Peng +1
In this paper, we aim to solve the high dimensional stochastic optimal control problem from the view of the stochastic maximum principle via deep learning. By introducing the exten…