The Importance of Pessimism in Fixed-Dataset Policy Optimization

15 September 2020

Papers citing "The Importance of Pessimism in Fixed-Dataset Policy Optimization"

40 / 90 papers shown

Title
Robust Anytime Learning of Markov Decision Processes Marnix Suilen T. D. Simão David Parker N. Jansen 8 13 0 31 May 2022
Non-Markovian policies occupancy measures Romain Laroche Rémi Tachet des Combes Jacob Buckman OffRL 29 1 0 27 May 2022
Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters Seyed Kamyar Seyed Ghasemipour S. Gu Ofir Nachum OffRL 23 69 0 27 May 2022
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes Miao Lu Yifei Min Zhaoran Wang Zhuoran Yang OffRL 51 22 0 26 May 2022
Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret Jiawei Huang Li Zhao Tao Qin Wei-Neng Chen Nan Jiang Tie-Yan Liu OffRL 16 3 0 25 May 2022
Offline Policy Comparison with Confidence: Benchmarks and Baselines Anurag Koul Mariano Phielipp Alan Fern OffRL 20 0 0 22 May 2022
Bellman Residual Orthogonalization for Offline Reinforcement Learning Andrea Zanette Martin J. Wainwright OffRL 22 8 0 24 Mar 2022
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity Laixi Shi Gen Li Yuting Wei Yuxin Chen Yuejie Chi OffRL 26 90 0 28 Feb 2022
Robust Imitation Learning from Corrupted Demonstrations Liu Liu Ziyang Tang Lanqing Li Dijun Luo 28 12 0 29 Jan 2022
Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers? Han Zhong Zhuoran Yang Zhaoran Wang Michael I. Jordan 29 30 0 27 Dec 2021
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization Thanh Nguyen-Tang Sunil R. Gupta A. Nguyen Svetha Venkatesh OffRL 24 28 0 27 Nov 2021
The Difficulty of Passive Learning in Deep Reinforcement Learning Georg Ostrovski P. S. Castro Will Dabney OffRL 11 57 0 26 Oct 2021
Towards Instance-Optimal Offline Reinforcement Learning with Pessimism Ming Yin Yu-Xiang Wang OffRL 24 82 0 17 Oct 2021
Value Penalized Q-Learning for Recommender Systems Chengqian Gao Ke Xu Kuangqi Zhou Lanqing Li Xueqian Wang Bo Yuan P. Zhao OffRL 50 20 0 15 Oct 2021
Offline Reinforcement Learning with Soft Behavior Regularization Haoran Xu Xianyuan Zhan Jianxiong Li Honglei Yin OffRL 18 31 0 14 Oct 2021
You Only Evaluate Once: a Simple Baseline Algorithm for Offline RL Wonjoon Goo S. Niekum OffRL 35 8 0 05 Oct 2021
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning Andrea Zanette Martin J. Wainwright Emma Brunskill OffRL 29 111 0 19 Aug 2021
Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage Masatoshi Uehara Wen Sun OffRL 96 144 0 13 Jul 2021
The Curse of Passive Data Collection in Batch Reinforcement Learning Chenjun Xiao Ilbin Lee Bo Dai Dale Schuurmans Csaba Szepesvári OffRL 17 1 0 18 Jun 2021
Offline RL Without Off-Policy Evaluation David Brandfonbrener William F. Whitney Rajesh Ranganath Joan Bruna OffRL 42 161 0 16 Jun 2021
A Minimalist Approach to Offline Reinforcement Learning Scott Fujimoto S. Gu OffRL 20 778 0 12 Jun 2021
Corruption-Robust Offline Reinforcement Learning Xuezhou Zhang Yiding Chen Jerry Zhu Wen Sun OffRL 38 39 0 11 Jun 2021
Offline Reinforcement Learning as Anti-Exploration Shideh Rezaeifar Robert Dadashi Nino Vieillard Léonard Hussenot Olivier Bachem Olivier Pietquin M. Geist OffRL 32 51 0 11 Jun 2021
Mitigating Covariate Shift in Imitation Learning via Offline Data Without Great Coverage Jonathan D. Chang Masatoshi Uehara Dhruv Sreenivas Rahul Kidambi Wen Sun OffRL 22 32 0 06 Jun 2021
Model-Based Offline Planning with Trajectory Pruning Xianyuan Zhan Xiangyu Zhu Haoran Xu OffRL 35 36 0 16 May 2021
On the Optimality of Batch Policy Optimization Algorithms Chenjun Xiao Yifan Wu Tor Lattimore Bo Dai Jincheng Mei Lihong Li Csaba Szepesvári Dale Schuurmans OffRL 28 33 0 06 Apr 2021
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism Paria Rashidinejad Banghua Zhu Cong Ma Jiantao Jiao Stuart J. Russell OffRL 28 273 0 22 Mar 2021
Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks Thanh Nguyen-Tang Sunil R. Gupta Hung The Tran Svetha Venkatesh OffRL 57 7 0 11 Mar 2021
S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning Samarth Sinha Ajay Mandlekar Animesh Garg OffRL 24 104 0 10 Mar 2021
Offline Reinforcement Learning with Pseudometric Learning Robert Dadashi Shideh Rezaeifar Nino Vieillard Léonard Hussenot Olivier Pietquin M. Geist OffRL 31 40 0 02 Mar 2021
Uncertainty Estimation Using Riemannian Model Dynamics for Offline Reinforcement Learning Guy Tennenholtz Shie Mannor OffRL 18 11 0 22 Feb 2021
Continuous Doubly Constrained Batch Reinforcement Learning Rasool Fakoor Jonas W. Mueller Kavosh Asadi Pratik Chaudhari Alex Smola OffRL 204 27 0 18 Feb 2021
Risk-Averse Offline Reinforcement Learning Núria Armengol Urpí Sebastian Curi Andreas Krause OffRL 6 70 0 10 Feb 2021
Is Pessimism Provably Efficient for Offline RL? Ying Jin Zhuoran Yang Zhaoran Wang OffRL 27 346 0 30 Dec 2020
Offline Policy Selection under Uncertainty Mengjiao Yang Bo Dai Ofir Nachum George Tucker Dale Schuurmans OffRL 6 32 0 12 Dec 2020
Revisiting Rainbow: Promoting more Insightful and Inclusive Deep Reinforcement Learning Research J. Obando-Ceron P. S. Castro OffRL 9 105 0 20 Nov 2020
Reliable Off-policy Evaluation for Reinforcement Learning Jie Wang Rui Gao H. Zha OffRL 17 11 0 08 Nov 2020
CoinDICE: Off-Policy Confidence Interval Estimation Bo Dai Ofir Nachum Yinlam Chow Lihong Li Csaba Szepesvári Dale Schuurmans OffRL 24 84 0 22 Oct 2020
DeepAveragers: Offline Reinforcement Learning by Solving Derived Non-Parametric MDPs Aayam Shrestha Stefan Lee Prasad Tadepalli Alan Fern OffRL 55 23 0 18 Oct 2020
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine Aviral Kumar George Tucker Justin Fu OffRL GP 340 1,955 0 04 May 2020