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Offline Reinforcement Learning (RL) aims to turn large datasets into powerful decision-making engines without any online interactions with the environment.
Benchmarking batch deep reinforcement learning algorithms
Scott Fujimoto, Edoardo Conti, Mohammad Ghavamzadeh, and Joelle Pineau · 1910
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Causality
Judea Pearl · 2009
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Playing atari with deep reinforcement learning
V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, Ioannis Antonoglou, Daan Wierstra, and Martin A. Riedmiller · 2013
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Minimalistic gridworld environment for openai gym
Maxime Chevalier-Boisvert, Lucas Willems, and Suman Pal · 2018
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Addressing function approximation error in actor-critic methods
Scott Fujimoto, H. V. Hoof, and David Meger · 2018
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
T. Haarnoja, Aurick Zhou, P. Abbeel, and S. Levine · 2018
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Stabilizing off-policy q-learning via bootstrapping error reduction
A. Kumar, Justin Fu, G. Tucker, and S. Levine · 2019
Cited alongside, same era.
Behavior regularized offline reinforcement learning
Y. Wu, G. Tucker, and Ofir Nachum · 2019
Cited alongside, same era.
Qd-rl: Efficient mixing of quality and diversity in reinforcement learning
Geoffrey Cideron, Thomas Pierrot, N. Perrin, Karim Beguir, and Olivier Sigaud · 2020
Cited alongside, same era.
D4rl: Datasets for deep data-driven reinforcement learning
Justin Fu, Aviral Kumar, Ofir Nachum, G. Tucker, and Sergey Levine · 2020
Cited alongside, same era.
Emaq: Expected-max q-learning operator for simple yet effective offline and online rl
Conservative q-learning for offline reinforcement learning
Aviral Kumar, Aurick Zhou, G. Tucker, and Sergey Levine · 2020
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Offline reinforcement learning: Tutorial, review, and perspectives on open problems
Sergey Levine, Aviral Kumar, George Tucker, and Justin Fu · 2020
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Accelerating online reinforcement learning with offline datasets
Ashvin Nair, Murtaza Dalal, Abhishek Gupta, and Sergey Levine · 2020
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Keep doing what worked: Behavioral modelling priors for offline reinforcement learning
Noah Siegel, Jost Tobias Springenberg, Felix Berkenkamp, Abbas Abdolmaleki, Michael Neunert, T. Lampe, Roland Hafner, and Martin A. Riedmiller · 2020
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Seyed Kamyar Seyed Ghasemipour, Dale Schuurmans, and Shixiang Gu · 2020
Cited alongside, same era.
Rl unplugged: Benchmarks for offline reinforcement learning
Caglar Gulcehre, Ziyu Wang, A. Novikov, T. L. Paine, Sergio Gomez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, J. Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, G. Tucker, Nicolas Heess, and N. D. Freitas · 2020
Cited alongside, same era.
Off-policy deep reinforcement learning without exploration
Scott Fujimoto, D. Meger, and Doina Precup
Cited in the paper.
Ziyu Wang, A. Novikov, Konrad Zolna, Jost Tobias Springenberg, Scott Reed, B. Shahriari, N. Siegel, Josh Merel, Caglar Gulcehre, Nicolas Heess, and N. D. Freitas · 2020
Closest in time.