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A Workflow for Offline Model-Free Robotic Reinforcement Learning


Sep 23, 2021
Aviral Kumar, Anikait Singh, Stephen Tian, Chelsea Finn, Sergey Levine

* CoRL 2021. Project Website: https://sites.google.com/view/offline-rl-workflow. First two authors contributed equally 

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Conservative Data Sharing for Multi-Task Offline Reinforcement Learning


Sep 16, 2021
Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn


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Conservative Objective Models for Effective Offline Model-Based Optimization


Jul 14, 2021
Brandon Trabucco, Aviral Kumar, Xinyang Geng, Sergey Levine

* ICML 2021. First two authors contributed equally. Code at: https://github.com/brandontrabucco/design-baselines/blob/c65a53fe1e6567b740f0adf60c5db9921c1f2330/design_baselines/coms_cleaned/__init__.py 

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Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability


Jul 13, 2021
Dibya Ghosh, Jad Rahme, Aviral Kumar, Amy Zhang, Ryan P. Adams, Sergey Levine

* First two authors contributed equally 

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Benchmarks for Deep Off-Policy Evaluation


Mar 30, 2021
Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine

* ICLR 2021 paper. Policies and evaluation code are available at https://github.com/google-research/deep_ope 

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COMBO: Conservative Offline Model-Based Policy Optimization


Feb 16, 2021
Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn


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COG: Connecting New Skills to Past Experience with Offline Reinforcement Learning


Oct 27, 2020
Avi Singh, Albert Yu, Jonathan Yang, Jesse Zhang, Aviral Kumar, Sergey Levine

* Accepted to CoRL 2020. Source code and videos available at https://sites.google.com/view/cog-rl 

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Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning


Oct 27, 2020
Aviral Kumar, Rishabh Agarwal, Dibya Ghosh, Sergey Levine

* Pre-print. First two authors contributed equally 

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Conservative Safety Critics for Exploration


Oct 27, 2020
Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart, Sergey Levine, Florian Shkurti, Animesh Garg

* Preprint. Under review 

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One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL


Oct 27, 2020
Saurabh Kumar, Aviral Kumar, Sergey Levine, Chelsea Finn

* Accepted at NeurIPS 2020 

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OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning


Oct 27, 2020
Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum

* https://sites.google.com/view/opal-iclr 

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Conservative Q-Learning for Offline Reinforcement Learning


Jun 29, 2020
Aviral Kumar, Aurick Zhou, George Tucker, Sergey Levine

* Preprint. Website at: https://sites.google.com/view/cql-offline-rl 

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Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems


May 04, 2020
Sergey Levine, Aviral Kumar, George Tucker, Justin Fu


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D4RL: Datasets for Deep Data-Driven Reinforcement Learning


Apr 20, 2020
Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, Sergey Levine

* Website available at https://sites.google.com/view/d4rl/home 

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Datasets for Data-Driven Reinforcement Learning


Apr 15, 2020
Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, Sergey Levine


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DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction


Mar 16, 2020
Aviral Kumar, Abhishek Gupta, Sergey Levine

* Pre-print 

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Reward-Conditioned Policies


Dec 31, 2019
Aviral Kumar, Xue Bin Peng, Sergey Levine


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Model Inversion Networks for Model-Based Optimization


Dec 31, 2019
Aviral Kumar, Sergey Levine


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Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning


Oct 07, 2019
Xue Bin Peng, Aviral Kumar, Grace Zhang, Sergey Levine


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Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction


Jun 03, 2019
Aviral Kumar, Justin Fu, George Tucker, Sergey Levine


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Graph Normalizing Flows


May 30, 2019
Jenny Liu, Aviral Kumar, Jimmy Ba, Jamie Kiros, Kevin Swersky


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Calibration of Encoder Decoder Models for Neural Machine Translation


Mar 03, 2019
Aviral Kumar, Sunita Sarawagi

* 12 Pages 

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Diagnosing Bottlenecks in Deep Q-learning Algorithms


Feb 26, 2019
Justin Fu, Aviral Kumar, Matthew Soh, Sergey Levine


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The Reach-Avoid Problem for Constant-Rate Multi-Mode Systems


Jul 12, 2017
Shankara Narayanan Krishna, Aviral Kumar, Fabio Somenzi, Behrouz Touri, Ashutosh Trivedi

* 26 pages 

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