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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.OC2021
Dynamic programming principle and Hamilton-Jacobi-Bellman equation under nonlinear expectation
Mingshang Hu, Shaolin Ji, Xiaojuan Li
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…
math.OC2021
A Modified Method of Successive Approximations for Stochastic Recursive Optimal Control Problems
Shaolin Ji, Rundong Xu
Based on the stochastic maximum principle for the partially coupled forward-backward stochastic control system (FBSCS for short), a modified method of successive approximations (MS…