Model-Based Reinforcement Learning with Value-Targeted Regression

1 June 2020

Papers citing "Model-Based Reinforcement Learning with Value-Targeted Regression"

50 / 223 papers shown

Title
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity Abhishek Gupta Aldo Pacchiano Yuexiang Zhai Sham Kakade Sergey Levine OffRL 41 66 0 18 Oct 2022
Bilinear Exponential Family of MDPs: Frequentist Regret Bound with Tractable Exploration and Planning Reda Ouhamma D. Basu Odalric-Ambrym Maillard OffRL 24 10 0 05 Oct 2022
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient Ming Yin Mengdi Wang Yu Wang OffRL 77 12 0 03 Oct 2022
Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation Dan Qiao Yu Wang OffRL 75 13 0 03 Oct 2022
A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning Zixiang Chen C. J. Li An Yuan Quanquan Gu Michael I. Jordan OffRL 116 26 0 30 Sep 2022
Proximal Point Imitation Learning Luca Viano Angeliki Kamoutsi Gergely Neu Igor Krawczuk V. Cevher 41 14 0 22 Sep 2022
Understanding Deep Neural Function Approximation in Reinforcement Learning via $ε$ -Greedy Exploration Fanghui Liu Luca Viano V. Cevher 42 16 0 15 Sep 2022
Learning Two-Player Mixture Markov Games: Kernel Function Approximation and Correlated Equilibrium C. J. Li Dongruo Zhou Quanquan Gu Michael I. Jordan 29 2 0 10 Aug 2022
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning Shuang Qiu Lingxiao Wang Chenjia Bai Zhuoran Yang Zhaoran Wang SSL OffRL 26 32 0 29 Jul 2022
A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation P. Amortila Nan Jiang Dhruv Madeka Dean Phillips Foster 29 5 0 18 Jul 2022
Model Selection in Reinforcement Learning with General Function Approximations Avishek Ghosh Sayak Ray Chowdhury 19 3 0 06 Jul 2022
Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design Andrew Wagenmaker Kevin G. Jamieson OffRL 32 26 0 06 Jul 2022
Provably Efficient Reinforcement Learning for Online Adaptive Influence Maximization Kaixuan Huang Yuehua Wu Xuezhou Zhang Shenyinying Tu Qingyun Wu Mengdi Wang Huazheng Wang 28 1 0 29 Jun 2022
On the Complexity of Adversarial Decision Making Dylan J. Foster Alexander Rakhlin Ayush Sekhari Karthik Sridharan AAML 31 28 0 27 Jun 2022
Provably Efficient Model-Free Constrained RL with Linear Function Approximation A. Ghosh Xingyu Zhou Ness B. Shroff 75 23 0 23 Jun 2022
Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation Pihe Hu Yu Chen Longbo Huang 11 34 0 23 Jun 2022
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity Alekh Agarwal Tong Zhang 50 22 0 15 Jun 2022
Regret Bounds for Information-Directed Reinforcement Learning Botao Hao Tor Lattimore OffRL 47 17 0 09 Jun 2022
Goal-Space Planning with Subgoal Models Chun-Ping Lo Kevin Roice Parham Mohammad Panahi Scott M. Jordan Adam White Gábor Mihucz Farzane Aminmansour Martha White 26 5 0 06 Jun 2022
Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning Dilip Arumugam Benjamin Van Roy OffRL 38 15 0 04 Jun 2022
Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning Souradip Chakraborty Amrit Singh Bedi Alec Koppel Brian M. Sadler Furong Huang Pratap Tokekar Tianyi Zhou 31 9 0 02 Jun 2022
Offline Reinforcement Learning with Differential Privacy Dan Qiao Yu Wang OffRL 41 23 0 02 Jun 2022
Stabilizing Q-learning with Linear Architectures for Provably Efficient Learning Andrea Zanette Martin J. Wainwright OOD 40 5 0 01 Jun 2022
Provable Benefits of Representational Transfer in Reinforcement Learning Alekh Agarwal Yuda Song Wen Sun Kaiwen Wang Mengdi Wang Xuezhou Zhang OffRL 23 33 0 29 May 2022
Embed to Control Partially Observed Systems: Representation Learning with Provable Sample Efficiency Lingxiao Wang Qi Cai Zhuoran Yang Zhaoran Wang 64 17 0 26 May 2022
Computationally Efficient Horizon-Free Reinforcement Learning for Linear Mixture MDPs Dongruo Zhou Quanquan Gu 81 44 0 23 May 2022
Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation Xiaoyu Chen Han Zhong Zhuoran Yang Zhaoran Wang Liwei Wang 128 62 0 23 May 2022
Slowly Changing Adversarial Bandit Algorithms are Efficient for Discounted MDPs Ian A. Kash L. Reyzin Zishun Yu 31 0 0 18 May 2022
Control-Aware Prediction Objectives for Autonomous Driving R. McAllister Blake Wulfe Jean Mercat Logan Ellis Sergey Levine Adrien Gaidon 32 22 0 28 Apr 2022
Provably Efficient Kernelized Q-Learning Shuang Liu H. Su MLT 27 4 0 21 Apr 2022
Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency Qi Cai Zhuoran Yang Zhaoran Wang 30 14 0 20 Apr 2022
When Is Partially Observable Reinforcement Learning Not Scary? Qinghua Liu Alan Chung Csaba Szepesvári Chi Jin 22 94 0 19 Apr 2022
Value Gradient weighted Model-Based Reinforcement Learning C. Voelcker Victor Liao Animesh Garg Amir-massoud Farahmand 25 29 0 04 Apr 2022
AKF-SR: Adaptive Kalman Filtering-based Successor Representation Parvin Malekzadeh Mohammad Salimibeni Ming Hou Arash Mohammadi Konstantinos N. Plataniotis 25 5 0 31 Mar 2022
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism Ming Yin Yaqi Duan Mengdi Wang Yu Wang OffRL 34 66 0 11 Mar 2022
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets Yifei Min Tianhao Wang Ruitu Xu Zhaoran Wang Michael I. Jordan Zhuoran Yang 33 21 0 07 Mar 2022
Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach Shuang Qiu Boxiang Lyu Qing-xin Meng Zhaoran Wang Zhuoran Yang Michael I. Jordan 11 5 0 25 Feb 2022
Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning Jibang Wu Zixuan Zhang Zhe Feng Zhaoran Wang Zhuoran Yang Michael I. Jordan Haifeng Xu 18 33 0 22 Feb 2022
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization Mirco Mutti Ric De Santi Emanuele Rossi J. Calderón Michael M. Bronstein Marcello Restelli 30 14 0 14 Feb 2022
Computational-Statistical Gaps in Reinforcement Learning D. Kane Sihan Liu Shachar Lovett G. Mahajan 14 5 0 11 Feb 2022
Provably Efficient Primal-Dual Reinforcement Learning for CMDPs with Non-stationary Objectives and Constraints Yuhao Ding Javad Lavaei 27 10 0 28 Jan 2022
Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes Andrew Wagenmaker Yifang Chen Max Simchowitz S. Du Kevin G. Jamieson 19 48 0 26 Jan 2022
Meta Learning MDPs with Linear Transition Models Robert Muller Aldo Pacchiano 28 3 0 21 Jan 2022
Differentially Private Reinforcement Learning with Linear Function Approximation Xingyu Zhou 33 25 0 18 Jan 2022
Exponential Family Model-Based Reinforcement Learning via Score Matching Gen Li Junbo Li Anmol Kabra Nathan Srebro Zhaoran Wang Zhuoran Yang 32 4 0 28 Dec 2021
Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers? Han Zhong Zhuoran Yang Zhaoran Wang Michael I. Jordan 31 30 0 27 Dec 2021
Differentially Private Regret Minimization in Episodic Markov Decision Processes Sayak Ray Chowdhury Xingyu Zhou 29 21 0 20 Dec 2021
Improved No-Regret Algorithms for Stochastic Shortest Path with Linear MDP Liyu Chen Rahul Jain Haipeng Luo 43 14 0 18 Dec 2021
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach Andrew Wagenmaker Yifang Chen Max Simchowitz S. Du Kevin G. Jamieson 73 37 0 07 Dec 2021
Differentially Private Exploration in Reinforcement Learning with Linear Representation Paul Luyo Evrard Garcelon A. Lazaric Matteo Pirotta 60 11 0 02 Dec 2021