Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias Function

12 June 2019

Papers citing "Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias Function"

27 / 27 papers shown

Title
Optimistic Q-learning for average reward and episodic reinforcement learning Priyank Agrawal Shipra Agrawal 56 4 0 18 Jul 2024
Reinforcement Learning and Regret Bounds for Admission Control Lucas Weber A. Busic Jiamin Zhu 35 0 0 07 Jun 2024
Dealing with unbounded gradients in stochastic saddle-point optimization Gergely Neu Nneka Okolo 39 3 0 21 Feb 2024
Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision Processes Réda Alami Mohammed Mahfoud Eric Moulines 24 2 0 01 Apr 2023
Reinforcement Learning in a Birth and Death Process: Breaking the Dependence on the State Space Jonatha Anselmi B. Gaujal Louis-Sébastien Rebuffi 32 2 0 21 Feb 2023
Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments Runlong Zhou Zihan Zhang S. Du 46 10 0 31 Jan 2023
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes Jiafan He Heyang Zhao Dongruo Zhou Quanquan Gu OffRL 56 55 0 12 Dec 2022
Near Sample-Optimal Reduction-based Policy Learning for Average Reward MDP Jinghan Wang Meng-Xian Wang Lin F. Yang 39 16 0 01 Dec 2022
Near-Optimal Regret Bounds for Multi-batch Reinforcement Learning Zihan Zhang Yuhang Jiang Yuanshuo Zhou Xiangyang Ji OffRL 26 9 0 15 Oct 2022
Provably Efficient Kernelized Q-Learning Shuang Liu H. Su MLT 34 4 0 21 Apr 2022
Horizon-Free Reinforcement Learning in Polynomial Time: the Power of Stationary Policies Zihan Zhang Xiangyang Ji S. Du 32 21 0 24 Mar 2022
Learning Infinite-Horizon Average-Reward Markov Decision Processes with Constraints Liyu Chen R. Jain Haipeng Luo 64 25 0 31 Jan 2022
Dueling RL: Reinforcement Learning with Trajectory Preferences Aldo Pacchiano Aadirupa Saha Jonathan Lee 38 82 0 08 Nov 2021
Settling the Horizon-Dependence of Sample Complexity in Reinforcement Learning Yuanzhi Li Ruosong Wang Lin F. Yang 29 20 0 01 Nov 2021
Learning Stochastic Shortest Path with Linear Function Approximation Steffen Czolbe Jiafan He Adrian Dalca Quanquan Gu 44 30 0 25 Oct 2021
Understanding Domain Randomization for Sim-to-real Transfer Xiaoyu Chen Jiachen Hu Chi Jin Lihong Li Liwei Wang 24 112 0 07 Oct 2021
A Bayesian Learning Algorithm for Unknown Zero-sum Stochastic Games with an Arbitrary Opponent Mehdi Jafarnia-Jahromi Rahul Jain A. Nayyar 41 5 0 08 Sep 2021
Sublinear Regret for Learning POMDPs Yi Xiong Ningyuan Chen Xuefeng Gao Xiang Zhou 29 25 0 08 Jul 2021
Online Learning for Unknown Partially Observable MDPs Mehdi Jafarnia-Jahromi Rahul Jain A. Nayyar 36 20 0 25 Feb 2021
Causal Markov Decision Processes: Learning Good Interventions Efficiently Yangyi Lu A. Meisami Ambuj Tewari 23 10 0 15 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
Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon Zihan Zhang Xiangyang Ji S. Du OffRL 36 104 0 28 Sep 2020
A Provably Efficient Sample Collection Strategy for Reinforcement Learning Jean Tarbouriech Matteo Pirotta Michal Valko A. Lazaric OffRL 27 16 0 13 Jul 2020
Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism Wang Chi Cheung D. Simchi-Levi Ruihao Zhu OffRL 22 93 0 24 Jun 2020
Tightening Exploration in Upper Confidence Reinforcement Learning Hippolyte Bourel Odalric-Ambrym Maillard M. S. Talebi 30 31 0 20 Apr 2020
Learning Near Optimal Policies with Low Inherent Bellman Error Andrea Zanette A. Lazaric Mykel Kochenderfer Emma Brunskill OffRL 27 221 0 29 Feb 2020
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes Chen-Yu Wei Mehdi Jafarnia-Jahromi Haipeng Luo Hiteshi Sharma R. Jain 107 100 0 15 Oct 2019