most citedLearning to Communicate: A Machine Learning Framework for Heterogeneous Multi-Agent Robotic Systems

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math.OC20211 cited

On the Semidefinite Duality of Finite-Horizon LQG Problem

Donghwan Lee

In this paper, our goal is to study fundamental foundations of linear quadratic Gaussian (LQG) control problems for stochastic linear time-invariant systems via Lagrangian duality…

math.OC2021

Convergence of Dynamic Programming on the Semidefinite Cone

Donghwan Lee

The goal of this paper is to investigate new and simple convergence analysis of dynamic programming for linear quadratic regulator problem of discrete-time linear time-invariant sy…

math.OC2021

Data-Driven Control Design with LMIs and Dynamic Programming

Donghwan Lee, Do Wan Kim

The goal of this paper is to develop data-driven control design and evaluation strategies based on linear matrix inequalities (LMIs) and dynamic programming. We consider determinis…

math.OC2021

Multi-Objective LQG Design with Primal-Dual Method

Donghwan Lee, Do Wan Kim

The goal of this paper is to study a multi-objective linear quadratic Gaussian (LQG) control problem. In particular, we consider an optimal control problem minimizing a quadratic c…

math.OC2018

Supplemental Material For "Primal-Dual Q-Learning Framework for LQR Design"

Donghwan Lee, Jianghai Hu

Recently, reinforcement learning (RL) is receiving more and more attentions due to its successful demonstrations outperforming human performance in certain challenging tasks. In ou…

math.OC2018

Dynamic Programming for POMDP with Jointly Discrete and Continuous State-Spaces

Donghwan Lee, Niao He, Jianghai Hu

In this work, we study dynamic programming (DP) algorithms for partially observable Markov decision processes with jointly continuous and discrete state-spaces. We consider a class…