activity
20132023
most citedConsensus Seeking in Multi-Agent Systems with Multiplicative Measurement Noises

135 citations · 147 across the 10 of their papers we have counts for

collaborators

14 papers

math.OC2023

Solving Coupled Nonlinear Forward-backward Stochastic Differential Equations: An Optimization Perspective with Backward Measurability Loss

Yutian Wang, Yuan-Hua Ni, Xun Li

This paper aims to extend the BML method proposed in Wang et al. [22] to make it applicable to more general coupled nonlinear FBSDEs. We interpret BML from the fixed-point iteratio…

math.OC2023

Decentralized Stochastic Linear-Quadratic Optimal Control with Risk Constraint and Partial Observation

Jia Hui, Yuan-Hua Ni

This paper addresses a risk-constrained decentralized stochastic linear-quadratic optimal control problem with one remote controller and one local controller, where the risk constr…

math.OC2023

Accelerated Optimization Landscape of Linear-Quadratic Regulator

Lechen Feng, Yuan-Hua Ni

Linear-quadratic regulator (LQR) is a landmark problem in the field of optimal control, which is the concern of this paper. Generally, LQR is classified into state-feedback LQR (SL…

math.OC2022

Deterministic Dynamic Stackelberg Games: Time-Consistent Open-Loop Solution

Yuan-Hua Ni, Liping Liu, Xinzhen Zhang

In this paper, the known deterministic linear-quadratic Stackelberg game is revisited, whose open-loop Stackelberg solution actually possesses the nature of time inconsistency. To…

math.OC2022★ 1 cited

Deep BSDE-ML Learning and Its Application to Model-Free Optimal Control

Yutian Wang, Yuan-Hua Ni

A modified Deep BSDE (backward differential equation) learning method with measurability loss, called Deep BSDE-ML method, is introduced in this paper to solve a kind of linear dec…

math.OC2019

A Nash-Type Fictitious Game Framework to Time-Inconsistent Stochastic Control Problems

Yuan-Hua Ni, Binbin Si, Xinzhen Zhang

In this paper, a Nash-type fictitious game framework is introduced to handle a time-inconsistent linear-quadratic optimal control. The Nash-type game in this framework is called fi…