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SimGAN: Hybrid Simulator Identification for Domain Adaptation via Adversarial Reinforcement Learning

Jan 15, 2021
Yifeng Jiang, Tingnan Zhang, Daniel Ho, Yunfei Bai, C. Karen Liu, Sergey Levine, Jie Tan

* Submitted to ICRA 2021 

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Evolving Reinforcement Learning Algorithms

Jan 08, 2021
John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Sergey Levine, Quoc V. Le, Honglak Lee, Aleksandra Faust


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Model-Based Visual Planning with Self-Supervised Functional Distances

Dec 30, 2020
Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine


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ViNG: Learning Open-World Navigation with Visual Goals

Dec 17, 2020
Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine


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Variable-Shot Adaptation for Online Meta-Learning

Dec 14, 2020
Tianhe Yu, Xinyang Geng, Chelsea Finn, Sergey Levine

* First two authors contribute equally 

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WILDS: A Benchmark of in-the-Wild Distribution Shifts

Dec 14, 2020
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang


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Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning

Dec 08, 2020
Mohammad Babaeizadeh, Mohammad Taghi Saffar, Danijar Hafner, Harini Kannan, Chelsea Finn, Sergey Levine, Dumitru Erhan


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Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design

Dec 03, 2020
Michael Dennis, Natasha Jaques, Eugene Vinitsky, Alexandre Bayen, Stuart Russell, Andrew Critch, Sergey Levine


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Parrot: Data-Driven Behavioral Priors for Reinforcement Learning

Nov 19, 2020
Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine

* First two authors contributed equally. Project website: https://sites.google.com/view/parrot-rl 

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C-Learning: Learning to Achieve Goals via Recursive Classification

Nov 17, 2020
Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine

* Project website: https://ben-eysenbach.github.io/c_learning/ 

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Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Nov 12, 2020
Karl Schmeckpeper, Oleh Rybkin, Kostas Daniilidis, Sergey Levine, Chelsea Finn


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Continual Learning of Control Primitives: Skill Discovery via Reset-Games

Nov 10, 2020
Kelvin Xu, Siddharth Verma, Chelsea Finn, Sergey Levine

* To appear at NeurIPS 2020 

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Amortized Conditional Normalized Maximum Likelihood

Nov 05, 2020
Aurick Zhou, Sergey Levine


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Rearrangement: A Challenge for Embodied AI

Nov 03, 2020
Dhruv Batra, Angel X. Chang, Sonia Chernova, Andrew J. Davison, Jia Deng, Vladlen Koltun, Sergey Levine, Jitendra Malik, Igor Mordatch, Roozbeh Mottaghi, Manolis Savva, Hao Su

* Authors are listed in alphabetical order 

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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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$γ$-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction

Oct 27, 2020
Michael Janner, Igor Mordatch, Sergey Levine

* NeurIPS 2020. Project page at: https://people.eecs.berkeley.edu/~janner/gamma-models/ 

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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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MELD: Meta-Reinforcement Learning from Images via Latent State Models

Oct 26, 2020
Tony Z. Zhao, Anusha Nagabandi, Kate Rakelly, Chelsea Finn, Sergey Levine

* Accepted to CoRL 2020. Supplementary material at https://sites.google.com/view/meld-lsm/home . 16 pages, 19 figures 

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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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