Provably Efficient Reinforcement Learning with Linear Function
Approximation

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Provably Efficient Reinforcement Learning with Linear Function Approximation

11 July 2019

Michael I. Jordan

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Papers citing "Provably Efficient Reinforcement Learning with Linear Function Approximation"

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Title
Learning Near Optimal Policies with Low Inherent Bellman Error Andrea Zanette A. Lazaric Mykel Kochenderfer Emma Brunskill OffRL 116 222 0 29 Feb 2020
Agnostic Q-learning with Function Approximation in Deterministic Systems: Tight Bounds on Approximation Error and Sample Complexity S. Du Jason D. Lee G. Mahajan Ruosong Wang 57 37 0 17 Feb 2020
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium Qiaomin Xie Yudong Chen Zhaoran Wang Zhuoran Yang 175 127 0 17 Feb 2020
Adaptive Approximate Policy Iteration Botao Hao N. Lazić Yasin Abbasi-Yadkori Pooria Joulani Csaba Szepesvári 94 14 0 08 Feb 2020
Can Agents Learn by Analogy? An Inferable Model for PAC Reinforcement Learning Yanchao Sun Furong Huang 93 4 0 21 Dec 2019
Provably Efficient Reinforcement Learning with Aggregated States Shi Dong Benjamin Van Roy Zhengyuan Zhou 56 32 0 13 Dec 2019
Provably Efficient Exploration in Policy Optimization Qi Cai Zhuoran Yang Chi Jin Zhaoran Wang 113 283 0 12 Dec 2019
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 191 137 0 09 Dec 2019
Corruption-robust exploration in episodic reinforcement learning Thodoris Lykouris Max Simchowitz Aleksandrs Slivkins Wen Sun 107 105 0 20 Nov 2019
Learning with Good Feature Representations in Bandits and in RL with a Generative Model Tor Lattimore Csaba Szepesvári Gellert Weisz OffRL 193 171 0 18 Nov 2019
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration Andrea Zanette David Brandfonbrener Emma Brunskill Matteo Pirotta A. Lazaric 155 132 0 01 Nov 2019
Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles Aditya Modi Nan Jiang Ambuj Tewari Satinder Singh 72 133 0 23 Oct 2019
Zap Q-Learning With Nonlinear Function Approximation Shuhang Chen Adithya M. Devraj Fan Lu Ana Bušić Sean P. Meyn 67 20 0 11 Oct 2019
Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning? S. Du Sham Kakade Ruosong Wang Lin F. Yang 231 193 0 07 Oct 2019
$$\sqrt{n}$-Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank$ $\sqrt{n}$ -Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank Kefan Dong Jian-wei Peng Yining Wang Yuanshuo Zhou OffRL 81 36 0 05 Sep 2019
Global Optimality Guarantees For Policy Gradient Methods Jalaj Bhandari Daniel Russo 119 193 0 05 Jun 2019
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound Lin F. Yang Mengdi Wang OffRL GP 131 288 0 24 May 2019