Learning Near Optimal Policies with Low Inherent Bellman Error

29 February 2020

Mykel Kochenderfer

Papers citing "Learning Near Optimal Policies with Low Inherent Bellman Error"

50 / 71 papers shown

Title
Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation Taehyun Cho Seung Han Kyungjae Lee Seokhun Ju Dohyeong Kim Jungwoo Lee 72 0 0 31 Jul 2024
Offline RL via Feature-Occupancy Gradient Ascent Gergely Neu Nneka Okolo OffRL 34 0 0 22 May 2024
Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback Asaf B. Cassel Haipeng Luo Aviv A. Rosenberg Dmitry Sotnikov OffRL 33 3 0 13 May 2024
Horizon-Free Regret for Linear Markov Decision Processes Zihan Zhang Jason D. Lee Yuxin Chen Simon S. Du 33 3 0 15 Mar 2024
No-Regret Reinforcement Learning in Smooth MDPs Davide Maran Alberto Maria Metelli Matteo Papini Marcello Restell 38 4 0 06 Feb 2024
On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond Thanh Nguyen-Tang Raman Arora OffRL 38 3 0 06 Jan 2024
Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes Ruiquan Huang Yuan Cheng Jing Yang Vincent Tan Yingbin Liang 30 0 0 20 Oct 2023
Uncertainty-aware transfer across tasks using hybrid model-based successor feature reinforcement learning Parvin Malekzadeh Ming Hou Konstantinos N. Plataniotis 51 1 0 16 Oct 2023
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo Haque Ishfaq Qingfeng Lan Pan Xu A. R. Mahmood Doina Precup Anima Anandkumar Kamyar Azizzadenesheli BDL OffRL 30 20 0 29 May 2023
Does Sparsity Help in Learning Misspecified Linear Bandits? Jialin Dong Lin F. Yang 25 1 0 29 Mar 2023
Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs Yuan Cheng Ruiquan Huang J. Yang Yitao Liang OffRL 41 8 0 20 Mar 2023
Exponential Hardness of Reinforcement Learning with Linear Function Approximation Daniel M. Kane Sihan Liu Shachar Lovett G. Mahajan Csaba Szepesvári Gellert Weisz 48 3 0 25 Feb 2023
Provably Efficient Reinforcement Learning via Surprise Bound Hanlin Zhu Ruosong Wang Jason D. Lee OffRL 28 5 0 22 Feb 2023
Reinforcement Learning with Function Approximation: From Linear to Nonlinear Jihao Long Jiequn Han 39 5 0 20 Feb 2023
Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning Volodymyr Tkachuk Seyed Alireza Bakhtiari Johannes Kirschner Matej Jusup Ilija Bogunovic Csaba Szepesvári 32 5 0 08 Feb 2023
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation Uri Sherman Tomer Koren Yishay Mansour 34 12 0 30 Jan 2023
Near-optimal Policy Identification in Active Reinforcement Learning Xiang Li Viraj Mehta Johannes Kirschner I. Char Willie Neiswanger J. Schneider Andreas Krause Ilija Bogunovic OffRL 48 6 0 19 Dec 2022
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes Jiafan He Heyang Zhao Dongruo Zhou Quanquan Gu OffRL 53 55 0 12 Dec 2022
Model-Free Reinforcement Learning with the Decision-Estimation Coefficient Dylan J. Foster Noah Golowich Jian Qian Alexander Rakhlin Ayush Sekhari OffRL 40 9 0 25 Nov 2022
Linear Reinforcement Learning with Ball Structure Action Space Zeyu Jia Randy Jia Dhruv Madeka Dean Phillips Foster 31 1 0 14 Nov 2022
When is Realizability Sufficient for Off-Policy Reinforcement Learning? Andrea Zanette OffRL 24 14 0 10 Nov 2022
Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms Osama A. Hanna Lin F. Yang Christina Fragouli 27 11 0 08 Nov 2022
Efficient Global Planning in Large MDPs via Stochastic Primal-Dual Optimization Gergely Neu Nneka Okolo 42 6 0 21 Oct 2022
Distributionally Robust Offline Reinforcement Learning with Linear Function Approximation Xiaoteng Ma Zhipeng Liang Jose H. Blanchet MingWen Liu Li Xia Jiheng Zhang Qianchuan Zhao Zhengyuan Zhou OOD OffRL 41 22 0 14 Sep 2022
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning Christoph Dann M. Mohri Tong Zhang Julian Zimmert OffRL 23 33 0 23 Aug 2022
Future-Dependent Value-Based Off-Policy Evaluation in POMDPs Masatoshi Uehara Haruka Kiyohara Andrew Bennett Victor Chernozhukov Nan Jiang Nathan Kallus C. Shi Wen Sun OffRL 34 16 0 26 Jul 2022
A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation Philip Amortila Nan Jiang Dhruv Madeka Dean Phillips Foster 29 5 0 18 Jul 2022
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems Masatoshi Uehara Ayush Sekhari Jason D. Lee Nathan Kallus Wen Sun OffRL 51 32 0 24 Jun 2022
On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL Jinglin Chen Aditya Modi A. Krishnamurthy Nan Jiang Alekh Agarwal 38 25 0 21 Jun 2022
Sample-Efficient Reinforcement Learning of Partially Observable Markov Games Qinghua Liu Csaba Szepesvári Chi Jin 45 20 0 02 Jun 2022
Stabilizing Q-learning with Linear Architectures for Provably Efficient Learning Andrea Zanette Martin J. Wainwright OOD 45 5 0 01 Jun 2022
When Is Partially Observable Reinforcement Learning Not Scary? Qinghua Liu Alan Chung Csaba Szepesvári Chi Jin 22 94 0 19 Apr 2022
Jump-Start Reinforcement Learning Ikechukwu Uchendu Ted Xiao Yao Lu Banghua Zhu Mengyuan Yan ... Chuyuan Fu Cong Ma Jiantao Jiao Sergey Levine Karol Hausman OffRL OnRL 44 109 0 05 Apr 2022
Near-optimal Offline Reinforcement Learning with Linear Representation: Leveraging Variance Information with Pessimism Ming Yin Yaqi Duan Mengdi Wang Yu Wang OffRL 36 66 0 11 Mar 2022
A Complete Characterization of Linear Estimators for Offline Policy Evaluation Juan C. Perdomo A. Krishnamurthy Peter L. Bartlett Sham Kakade OffRL 29 3 0 08 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 35 21 0 07 Mar 2022
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback Tiancheng Jin Tal Lancewicki Haipeng Luo Yishay Mansour Aviv A. Rosenberg 74 21 0 31 Jan 2022
Exponential Family Model-Based Reinforcement Learning via Score Matching Gen Li Junbo Li Anmol Kabra Nathan Srebro Zhaoran Wang Zhuoran Yang 37 4 0 28 Dec 2021
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee Tianhao Wu Yunchang Yang Han Zhong Liwei Wang S. Du Jiantao Jiao 57 14 0 21 Dec 2021
Misspecified Gaussian Process Bandit Optimization Ilija Bogunovic Andreas Krause 57 43 0 09 Nov 2021
Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification Clémence Réda Andrea Tirinzoni Rémy Degenne 31 9 0 02 Nov 2021
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection Matteo Papini Andrea Tirinzoni Aldo Pacchiano Marcello Restelli A. Lazaric Matteo Pirotta 19 18 0 27 Oct 2021
Locally Differentially Private Reinforcement Learning for Linear Mixture Markov Decision Processes Chonghua Liao Jiafan He Quanquan Gu 27 17 0 19 Oct 2021
Optimistic Policy Optimization is Provably Efficient in Non-stationary MDPs Han Zhong Zhuoran Yang Zhaoran Wang Csaba Szepesvári 49 21 0 18 Oct 2021
Representation Learning for Online and Offline RL in Low-rank MDPs Masatoshi Uehara Xuezhou Zhang Wen Sun OffRL 67 127 0 09 Oct 2021
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning Andrea Zanette Martin J. Wainwright Emma Brunskill OffRL 34 115 0 19 Aug 2021
Efficient Local Planning with Linear Function Approximation Dong Yin Botao Hao Yasin Abbasi-Yadkori N. Lazić Csaba Szepesvári 34 19 0 12 Aug 2021
Towards General Function Approximation in Zero-Sum Markov Games Baihe Huang Jason D. Lee Zhaoran Wang Zhuoran Yang 33 47 0 30 Jul 2021
Variance-Aware Off-Policy Evaluation with Linear Function Approximation Yifei Min Tianhao Wang Dongruo Zhou Quanquan Gu OffRL 39 38 0 22 Jun 2021
Provably Efficient Representation Selection in Low-rank Markov Decision Processes: From Online to Offline RL Weitong Zhang Jiafan He Dongruo Zhou Amy Zhang Quanquan Gu OffRL 24 11 0 22 Jun 2021