activity
20142023
most citedA Stochastic Maximum Principle Approach for Reinforcement Learning with Parameterized Environment

6 citations · 13 across the 10 of their papers we have counts for

collaborators

10 papers

math.OC2023

Linear-Quadratic Optimal Control Problem for Mean-Field Stochastic Differential Equations with a Type of Random Coefficients

Hongwei Mei, Qingmeng Wei, Jiongmin Yong

Motivated by linear-quadratic optimal control problems (LQ problems, for short) for mean-field stochastic differential equations (SDEs, for short) with the coefficients containing…

math.OC2022★ 1 cited

Turnpike Properties for Mean-Field Linear-Quadratic Optimal Control Problems

Jingrui Sun, Jiongmin Yong

This paper is concerned with an optimal control problem for a mean-field linear stochastic differential equation with a quadratic functional in the infinite time horizon. Under sui…

math.OC2022★ 1 cited

Optimal Controls for Forward-Backward Stochastic Differential Equations: Time-Inconsistency and Time-Consistent Solutions

Hanxiao Wang, Jiongmin Yong, Chao Zhou

This paper is concerned with an optimal control problem for a forward-backward stochastic differential equation (FBSDE, for short) with a recursive cost functional determined by a…

math.OC2022★ 6 cited

A Stochastic Maximum Principle Approach for Reinforcement Learning with Parameterized Environment

Richard Archibald, Feng Bao, Jiongmin Yong

In this work, we introduce a stochastic maximum principle (SMP) approach for solving the reinforcement learning problem with the assumption that the unknowns in the environment can…

math.PR2022

Backward Stochastic Differential Equations and Backward Stochastic Volterra Integral Equations with Anticipating Generators

Hanxiao Wang, Jiongmin Yong, Chao Zhou

For a backward stochastic differential equation (BSDE, for short), when the generator is not progressively measurable, it might not admit adapted solutions, shown by an example. Ho…

math.OC2022

Spike Variations for Stochastic Volterra Integral Equations

Tianxiao Wang, Jiongmin Yong

Spike variation technique plays a crucial role in deriving Pontryagin's type maximum principle of optimal controls for differential equations of several types, including ordinary d…

math.OC2022

Linear-Quadratic Optimal Controls for Stochastic Volterra Integral Equations: Causal State Feedback and Path-Dependent Riccati Equations

Hanxiao Wang, Jiongmin Yong, Chao Zhou

A linear-quadratic optimal control problem for a forward stochastic Volterra integral equation (FSVIE, for short) is considered. Under the usual convexity conditions, open-loop opt…

math.OC2022★ 2 cited

Turnpike Properties for Stochastic Linear-Quadratic Optimal Control Problems

Jingrui Sun, Hanxiao Wang, Jiongmin Yong

This paper analyzes the limiting behavior of stochastic linear-quadratic optimal control problems in finite time horizon as . The so-called turnpike pro…

math.OC2021★ 2 cited

Causal State Feedback Representation for Linear Quadratic Optimal Control Problems of Singular Volterra Integral Equations

Shuo Han, Ping Lin, Jiongmin Yong

This paper is concerned with a linear quadratic optimal control for a class of singular Volterra integral equations. Under proper convexity conditions, optimal control uniquely exi…

math.AP2014★ 1 cited

Regularity Analysis for an Abstract System of Coupled Hyperbolic and Parabolic Equations

Jianghao Hao, Zhuangyi Liu, Jiongmin Yong

In this paper, we provide a complete regularity analysis for an abstract system of coupled hyperbolic and parabolic equations in a complex Hilbert space. We are able to decompose t…