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Offline Meta-Reinforcement Learning for Industrial Insertion


Oct 12, 2021
Tony Z. Zhao, Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Nicolas Heess, Jon Scholz, Stefan Schaal, Sergey Levine


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Offline Reinforcement Learning with Implicit Q-Learning


Oct 12, 2021
Ilya Kostrikov, Ashvin Nair, Sergey Levine


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Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World


Oct 11, 2021
Laura Smith, J. Chase Kew, Xue Bin Peng, Sehoon Ha, Jie Tan, Sergey Levine

* Project website: https://sites.google.com/berkeley.edu/fine-tuning-locomotion 

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Mismatched No More: Joint Model-Policy Optimization for Model-Based RL


Oct 06, 2021
Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov


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The Information Geometry of Unsupervised Reinforcement Learning


Oct 06, 2021
Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine


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Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets


Sep 27, 2021
Frederik Ebert, Yanlai Yang, Karl Schmeckpeper, Bernadette Bucher, Georgios Georgakis, Kostas Daniilidis, Chelsea Finn, Sergey Levine


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Training on Test Data with Bayesian Adaptation for Covariate Shift


Sep 27, 2021
Aurick Zhou, Sergey Levine


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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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Robust Predictable Control


Sep 07, 2021
Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine

* Project site with videos and code: https://ben-eysenbach.github.io/rpc 

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Fully Autonomous Real-World Reinforcement Learning for Mobile Manipulation


Aug 03, 2021
Charles Sun, Jędrzej Orbik, Coline Devin, Brian Yang, Abhishek Gupta, Glen Berseth, Sergey Levine

* 16 pages 

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ReLMM: Practical RL for Learning Mobile Manipulation Skills Using Only Onboard Sensors


Jul 28, 2021
Charles Sun, Jędrzej Orbik, Coline Devin, Brian Yang, Abhishek Gupta, Glen Berseth, Sergey Levine

* 17 pages 

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Persistent Reinforcement Learning via Subgoal Curricula


Jul 27, 2021
Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn


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Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment


Jul 21, 2021
Michael Chang, Sidhant Kaushik, Sergey Levine, Thomas L. Griffiths

* Long Presentation at the Thirty-eighth International Conference on Machine Learning (ICML) 2021. 21 pages, 11 figures. v2: updated acknowledgments. v3: clarified that the internal function nodes of the credit assignment mechanism are not considered O(1) 

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Offline Meta-Reinforcement Learning with Online Self-Supervision


Jul 19, 2021
Vitchyr H. Pong, Ashvin Nair, Laura Smith, Catherine Huang, Sergey Levine

* 10 pages, 6 figures 

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MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning


Jul 18, 2021
Kevin Li, Abhishek Gupta, Ashwin Reddy, Vitchyr Pong, Aurick Zhou, Justin Yu, Sergey Levine

* Accepted to ICML 2021. First two authors contributed equally 

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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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Explore and Control with Adversarial Surprise


Jul 12, 2021
Arnaud Fickinger, Natasha Jaques, Samyak Parajuli, Michael Chang, Nicholas Rhinehart, Glen Berseth, Stuart Russell, Sergey Levine


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Pragmatic Image Compression for Human-in-the-Loop Decision-Making


Jul 07, 2021
Siddharth Reddy, Anca D. Dragan, Sergey Levine


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Multi-Robot Deep Reinforcement Learning for Mobile Navigation


Jun 24, 2021
Katie Kang, Gregory Kahn, Sergey Levine


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Model-Based Reinforcement Learning via Latent-Space Collocation


Jun 24, 2021
Oleh Rybkin, Chuning Zhu, Anusha Nagabandi, Kostas Daniilidis, Igor Mordatch, Sergey Levine

* International Conference on Machine Learning (ICML), 2021. Videos and code at https://orybkin.github.io/latco/ 

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FitVid: Overfitting in Pixel-Level Video Prediction


Jun 24, 2021
Mohammad Babaeizadeh, Mohammad Taghi Saffar, Suraj Nair, Sergey Levine, Chelsea Finn, Dumitru Erhan


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Which Mutual-Information Representation Learning Objectives are Sufficient for Control?


Jun 14, 2021
Kate Rakelly, Abhishek Gupta, Carlos Florensa, Sergey Levine

* 18 pages, 11 figures 

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What Can I Do Here? Learning New Skills by Imagining Visual Affordances


Jun 13, 2021
Alexander Khazatsky, Ashvin Nair, Daniel Jing, Sergey Levine

* 10 pages, 10 figures. Presented at ICRA 2021. Project website: https://sites.google.com/view/val-rl 

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Reinforcement Learning as One Big Sequence Modeling Problem


Jun 03, 2021
Michael Janner, Qiyang Li, Sergey Levine


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