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"

21 / 71 papers shown

Title
Randomized Exploration for Reinforcement Learning with General Value Function Approximation Haque Ishfaq Qiwen Cui V. Nguyen Alex Ayoub Zhuoran Yang Zhaoran Wang Doina Precup Lin F. Yang 37 43 0 15 Jun 2021
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning Tengyang Xie Nan Jiang Huan Wang Caiming Xiong Yu Bai OffRL OnRL 44 162 0 09 Jun 2021
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces Chi Jin Qinghua Liu Tiancheng Yu 26 50 0 07 Jun 2021
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting Gen Li Yuxin Chen Yuejie Chi Yuantao Gu Yuting Wei OffRL 26 28 0 17 May 2021
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation Andrea Zanette Ching-An Cheng Alekh Agarwal 34 53 0 24 Mar 2021
An Exponential Lower Bound for Linearly-Realizable MDPs with Constant Suboptimality Gap Yuanhao Wang Ruosong Wang Sham Kakade OffRL 41 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
Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent States Shi Dong Benjamin Van Roy Zhengyuan Zhou 32 29 0 10 Feb 2021
Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms Chi Jin Qinghua Liu Sobhan Miryoosefi OffRL 38 215 0 01 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 with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 122 167 0 06 Jan 2021
Learning Adversarial Markov Decision Processes with Delayed Feedback Tal Lancewicki Aviv A. Rosenberg Yishay Mansour 43 32 0 29 Dec 2020
Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL Andrea Zanette OffRL 28 71 0 14 Dec 2020
Model-based Reinforcement Learning for Continuous Control with Posterior Sampling Ying Fan Yifei Ming 33 17 0 20 Nov 2020
On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces Zhuoran Yang Chi Jin Zhaoran Wang Mengdi Wang Michael I. Jordan 44 18 0 09 Nov 2020
Efficient Learning in Non-Stationary Linear Markov Decision Processes Ahmed Touati Pascal Vincent 42 29 0 24 Oct 2020
Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon Zihan Zhang Xiangyang Ji S. Du OffRL 34 104 0 28 Sep 2020
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration Andrea Zanette A. Lazaric Mykel J. Kochenderfer Emma Brunskill 36 64 0 18 Aug 2020
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping Dongruo Zhou Jiafan He Quanquan Gu 35 133 0 23 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
Optimism in Reinforcement Learning with Generalized Linear Function Approximation Yining Wang Ruosong Wang S. Du A. Krishnamurthy 137 135 0 09 Dec 2019