The Gap Between Model-Based and Model-Free Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint

9 December 2018

Stephen Tu

Benjamin Recht

Papers citing "The Gap Between Model-Based and Model-Free Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint"

22 / 72 papers shown

Title
Scalable Reinforcement Learning for Multi-Agent Networked Systems Guannan Qu Adam Wierman Na Li 24 33 0 05 Dec 2019
Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms Kaipeng Zhang Zhuoran Yang Tamer Basar 65 1,184 0 24 Nov 2019
Continuous Control with Contexts, Provably S. Du Ruosong Wang Mengdi Wang Lin F. Yang OffRL 11 4 0 30 Oct 2019
$Policy Optimization for $\mathcal{H}_2$ Linear Control with $\mathcal{H}_\infty$ Robustness Guarantee: Implicit Regularization and Global Convergence$ Policy Optimization for $\mathcal{H}_2$ Linear Control with $\mathcal{H}_\infty$ Robustness Guarantee: Implicit Regularization and Global Convergence Kaipeng Zhang Bin Hu Tamer Basar 24 119 0 21 Oct 2019
Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games Zuyue Fu Zhuoran Yang Yongxin Chen Zhaoran Wang 27 54 0 16 Oct 2019
Analyzing the Variance of Policy Gradient Estimators for the Linear-Quadratic Regulator James A. Preiss Sébastien M. R. Arnold Chengdong Wei Marius Kloft OffRL 8 5 0 02 Oct 2019
Neural Policy Gradient Methods: Global Optimality and Rates of Convergence Lingxiao Wang Qi Cai Zhuoran Yang Zhaoran Wang 25 236 0 29 Aug 2019
On the Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost Zhuoran Yang Yongxin Chen Mingyi Hong Zhaoran Wang 37 39 0 14 Jul 2019
From self-tuning regulators to reinforcement learning and back again Nikolai Matni Alexandre Proutiere Anders Rantzer Stephen Tu 27 88 0 27 Jun 2019
Variance-reduced $Q$ -learning is minimax optimal Martin J. Wainwright OffRL 22 89 0 11 Jun 2019
Robust exploration in linear quadratic reinforcement learning Jack Umenberger Mina Ferizbegovic Thomas B. Schon H. Hjalmarsson 23 38 0 04 Jun 2019
Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games Kaipeng Zhang Zhuoran Yang Tamer Basar 32 125 0 31 May 2019
Safety Augmented Value Estimation from Demonstrations (SAVED): Safe Deep Model-Based RL for Sparse Cost Robotic Tasks Brijen Thananjeyan Ashwin Balakrishna Ugo Rosolia Felix Li R. McAllister Joseph E. Gonzalez Sergey Levine Francesco Borrelli Ken Goldberg OffRL 22 4 0 31 May 2019
Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator K. Krauth Stephen Tu Benjamin Recht 27 57 0 30 May 2019
$Stochastic approximation with cone-contractive operators: Sharp $\ell_\infty$-bounds for $Q$-learning$ Stochastic approximation with cone-contractive operators: Sharp $\ell_\infty$ -bounds for $Q$ -learning Martin J. Wainwright 14 104 0 15 May 2019
Efficient Model-free Reinforcement Learning in Metric Spaces Zhao Song Wen Sun OffRL 9 39 0 01 May 2019
A General Framework for Structured Learning of Mechanical Systems Jayesh K. Gupta Kunal Menda Zachary Manchester Mykel J. Kochenderfer AI4CE 13 35 0 22 Feb 2019
Certainty Equivalence is Efficient for Linear Quadratic Control Horia Mania Stephen Tu Benjamin Recht 12 74 0 21 Feb 2019
Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective Anirudh Vemula Wen Sun J. Andrew Bagnell 19 40 0 31 Jan 2019
Sample Complexity of Estimating the Policy Gradient for Nearly Deterministic Dynamical Systems Osbert Bastani 22 4 0 24 Jan 2019
On the Global Convergence of Imitation Learning: A Case for Linear Quadratic Regulator Qi Cai Mingyi Hong Yongxin Chen Zhaoran Wang 37 34 0 11 Jan 2019
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems Dhruv Malik A. Pananjady Kush S. Bhatia K. Khamaru Peter L. Bartlett Martin J. Wainwright 20 198 0 20 Dec 2018