Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles

23 October 2019

Papers citing "Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles"

36 / 36 papers shown

Title
Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games Tong Yang Bo Dai Lin Xiao Yuejie Chi OffRL 66 2 0 13 Feb 2025
Horizon-Free Regret for Linear Markov Decision Processes Zihan Zhang Jason D. Lee Yuxin Chen Simon S. Du 33 3 0 15 Mar 2024
The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions Nishil Patel Sebastian Lee Stefano Sarao Mannelli Sebastian Goldt Adrew Saxe OffRL 38 3 0 17 Jun 2023
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes Han Zhong Tong Zhang 35 26 0 15 May 2023
The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms Anirudh Vemula Yuda Song Aarti Singh J. Andrew Bagnell Sanjiban Choudhury OffRL 38 13 0 01 Mar 2023
Exponential Hardness of Reinforcement Learning with Linear Function Approximation Daniel M. Kane Sihan Liu Shachar Lovett G. Mahajan Csaba Szepesvári Gellert Weisz 46 3 0 25 Feb 2023
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation Uri Sherman Tomer Koren Yishay Mansour 32 12 0 30 Jan 2023
Tight Guarantees for Interactive Decision Making with the Decision-Estimation Coefficient Dylan J. Foster Noah Golowich Yanjun Han OffRL 30 29 0 19 Jan 2023
Understanding the Complexity Gains of Single-Task RL with a Curriculum Qiyang Li Yuexiang Zhai Yi Ma Sergey Levine 37 14 0 24 Dec 2022
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes Jiafan He Heyang Zhao Dongruo Zhou Quanquan Gu OffRL 51 53 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 38 9 0 25 Nov 2022
Tractable Optimality in Episodic Latent MABs Jeongyeol Kwon Yonathan Efroni C. Caramanis Shie Mannor 52 3 0 05 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
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
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity Alekh Agarwal Tong Zhang 50 22 0 15 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
Provably Efficient Kernelized Q-Learning Shuang Liu H. Su MLT 27 4 0 21 Apr 2022
Offline Reinforcement Learning Under Value and Density-Ratio Realizability: The Power of Gaps Jinglin Chen Nan Jiang OffRL 23 34 0 25 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
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
Learning Stochastic Shortest Path with Linear Function Approximation Steffen Czolbe Jiafan He Adrian Dalca Quanquan Gu 41 30 0 25 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 42 21 0 18 Oct 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 22 11 0 22 Jun 2021
An Exponential Lower Bound for Linearly-Realizable MDPs with Constant Suboptimality Gap Yuanhao Wang Ruosong Wang Sham Kakade OffRL 39 43 0 23 Mar 2021
Near-optimal Policy Optimization Algorithms for Learning Adversarial Linear Mixture MDPs Jiafan He Dongruo Zhou Quanquan Gu 95 24 0 17 Feb 2021
Model-free Representation Learning and Exploration in Low-rank MDPs Aditya Modi Jinglin Chen A. Krishnamurthy Nan Jiang Alekh Agarwal OffRL 102 78 0 14 Feb 2021
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP Zihan Zhang Jiaqi Yang Xiangyang Ji S. Du 71 38 0 29 Jan 2021
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping Dongruo Zhou Jiafan He Quanquan Gu 30 133 0 23 Jun 2020
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs Alekh Agarwal Sham Kakade A. Krishnamurthy Wen Sun OffRL 41 223 0 18 Jun 2020
Model-Based Reinforcement Learning with Value-Targeted Regression Alex Ayoub Zeyu Jia Csaba Szepesvári Mengdi Wang Lin F. Yang OffRL 36 299 0 01 Jun 2020
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension Ruosong Wang Ruslan Salakhutdinov Lin F. Yang 23 55 0 21 May 2020
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization Dongsheng Ding Xiaohan Wei Zhuoran Yang Zhaoran Wang M. Jovanović 20 159 0 01 Mar 2020
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 135 135 0 09 Dec 2019
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning Dipendra Kumar Misra Mikael Henaff A. Krishnamurthy John Langford 29 151 0 13 Nov 2019