Near-Optimal Randomized Exploration for Tabular Markov Decision
Processes

Near-Optimal Randomized Exploration for Tabular Markov Decision Processes

19 February 2021

Qiwen Cui

Papers citing "Near-Optimal Randomized Exploration for Tabular Markov Decision Processes"

11 / 11 papers shown

Title
Settling the Sample Complexity of Online Reinforcement Learning Zihan Zhang Yuxin Chen Jason D. Lee S. Du OffRL 133 22 0 25 Jul 2023
Breaking the Sample Complexity Barrier to Regret-Optimal Model-Free Reinforcement Learning Gen Li Laixi Shi Yuxin Chen Yuejie Chi OffRL 56 51 0 09 Oct 2021
Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration Priyank Agrawal Jinglin Chen Nan Jiang 55 19 0 23 Oct 2020
$Q$ -learning with Logarithmic Regret Kunhe Yang Lin F. Yang S. Du 57 59 0 16 Jun 2020
Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP Kefan Dong Yuanhao Wang Xiaoyu Chen Liwei Wang OffRL 42 95 0 27 Jan 2019
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds Andrea Zanette Emma Brunskill OffRL 93 274 0 01 Jan 2019
Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes Ronan Fruit Matteo Pirotta A. Lazaric 36 61 0 06 Jul 2018
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning Christoph Dann Tor Lattimore Emma Brunskill 67 307 0 22 Mar 2017
Deep Exploration via Randomized Value Functions Ian Osband Benjamin Van Roy Daniel Russo Zheng Wen 79 302 0 22 Mar 2017
Why is Posterior Sampling Better than Optimism for Reinforcement Learning? Ian Osband Benjamin Van Roy BDL 76 257 0 01 Jul 2016
Thompson Sampling: An Asymptotically Optimal Finite Time Analysis E. Kaufmann N. Korda Rémi Munos 119 585 0 18 May 2012