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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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LaND: Learning to Navigate from Disengagements

Oct 09, 2020
Gregory Kahn, Pieter Abbeel, Sergey Levine


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Multi-agent Social Reinforcement Learning Improves Generalization

Oct 01, 2020
Kamal Ndousse, Douglas Eck, Sergey Levine, Natasha Jaques

* 12 pages, 11 figures 

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Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings

Aug 15, 2020
Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman

* 15 pages, 8 figures, ICML 2020. Website with code: https://sites.google.com/berkeley.edu/carl 

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Offline Meta-Reinforcement Learning with Advantage Weighting

Aug 13, 2020
Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn

* 8 pages main text; 18 pages total 

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Assisted Perception: Optimizing Observations to Communicate State

Aug 06, 2020
Siddharth Reddy, Sergey Levine, Anca D. Dragan


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Adaptive Risk Minimization: A Meta-Learning Approach for Tackling Group Shift

Jul 06, 2020
Marvin Zhang, Henrik Marklund, Abhishek Gupta, Sergey Levine, Chelsea Finn

* Project website: https://sites.google.com/view/adaptive-risk-minimization ; Code: https://github.com/henrikmarklund/arm 

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Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions

Jul 05, 2020
Michael Chang, Sidhant Kaushik, S. Matthew Weinberg, Thomas L. Griffiths, Sergey Levine

* 17 pages, 12 figures, accepted to the International Conference on Machine Learning (ICML) 2020 

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Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems

Jun 30, 2020
Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Sergey Levine, Charles Blundell, Yoshua Bengio, Michael Mozer

* Under Review, NeurIPS 2020 

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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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Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?

Jun 26, 2020
Angelos Filos, Panagiotis Tigas, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, Yarin Gal

* Camera-ready version, International Conference of Machine Learning 2020 

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Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers

Jun 24, 2020
Benjamin Eysenbach, Swapnil Asawa, Shreyas Chaudhari, Ruslan Salakhutdinov, Sergey Levine


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Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors

Jun 23, 2020
Karl Pertsch, Oleh Rybkin, Frederik Ebert, Chelsea Finn, Dinesh Jayaraman, Sergey Levine

* Project page: orybkin.github.io/video-gcp 

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Simple and Effective VAE Training with Calibrated Decoders

Jun 23, 2020
Oleh Rybkin, Kostas Daniilidis, Sergey Levine

* Project website: \url{https://orybkin.github.io/sigma-vae/

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Ecological Reinforcement Learning

Jun 22, 2020
John D. Co-Reyes, Suvansh Sanjeev, Glen Berseth, Abhishek Gupta, Sergey Levine

* Preprint. Website at: https://sites.google.com/view/ecological-rl/home 

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Learning Invariant Representations for Reinforcement Learning without Reconstruction

Jun 18, 2020
Amy Zhang, Rowan McAllister, Roberto Calandra, Yarin Gal, Sergey Levine


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Accelerating Online Reinforcement Learning with Offline Datasets

Jun 16, 2020
Ashvin Nair, Murtaza Dalal, Abhishek Gupta, Sergey Levine

* 16 pages. Website: https://awacrl.github.io/ 

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RL-CycleGAN: Reinforcement Learning Aware Simulation-To-Real

Jun 16, 2020
Kanishka Rao, Chris Harris, Alex Irpan, Sergey Levine, Julian Ibarz, Mohi Khansari

* Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2020) 

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Meta-Reinforcement Learning Robust to Distributional Shift via Model Identification and Experience Relabeling

Jun 15, 2020
Russell Mendonca, Xinyang Geng, Chelsea Finn, Sergey Levine


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MOPO: Model-based Offline Policy Optimization

May 27, 2020
Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Zou, Sergey Levine, Chelsea Finn, Tengyu Ma

* First two authors contributed equally. Last two authors advised equally 

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Meta-Reinforcement Learning for Robotic Industrial Insertion Tasks

May 23, 2020
Gerrit Schoettler, Ashvin Nair, Juan Aparicio Ojea, Sergey Levine, Eugen Solowjow

* 9 pages, 8 figures 

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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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Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning

Apr 27, 2020
Archit Sharma, Michael Ahn, Sergey Levine, Vikash Kumar, Karol Hausman, Shixiang Gu


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The Ingredients of Real-World Robotic Reinforcement Learning

Apr 27, 2020
Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine

* First three authors contributed equally. Accepted as a spotlight presentation at ICLR 2020 

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Thinking While Moving: Deep Reinforcement Learning with Concurrent Control

Apr 25, 2020
Ted Xiao, Eric Jang, Dmitry Kalashnikov, Sergey Levine, Julian Ibarz, Karol Hausman, Alexander Herzog

* Published as a conference paper at ICLR 2020 

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The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget

Apr 24, 2020
Anirudh Goyal, Yoshua Bengio, Matthew Botvinick, Sergey Levine

* Published as a conference paper at ICLR 2020 

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