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Natural language is perhaps the most flexible and intuitive way for humans to communicate tasks to a robot.
Learning latent plans from play
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Mujoco: A physics engine for model-based control
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Action-conditional video prediction using deep networks in atari games
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Maximum entropy deep inverse reinforcement learning
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Guided cost learning: Deep inverse optimal control via policy optimization
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Generative adversarial imitation learning
Jonathan Ho and Stefano Ermon · 2016
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Hindsight experience replay
Marcin Andrychowicz, Filip Wolski, Alex Ray, Jonas Schneider, Rachel Fong, Peter Welinder, Bob McGrew, Josh Tobin, OpenAI Pieter Abbeel, and Wojciech Zaremba · 2017
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Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates
Shixiang Gu, Ethan Holly, Timothy Lillicrap, and Sergey Levine · 2017
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Multi-modal imitation learning from unstructured demonstrations using generative adversarial nets
Karol Hausman, Yevgen Chebotar, Stefan Schaal, Gaurav Sukhatme, and Joseph Lim · 2017
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Grounded language learning in a simulated 3d world
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Deep imitation learning for complex manipulation tasks from virtual reality teleoperation
Tianhao Zhang, Zoe McCarthy, Owen Jow, Dennis Lee, Xi Chen, Ken Goldberg, and Pieter Abbeel · 2018
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Goal-conditioned imitation learning
Yiming Ding, Carlos Florensa, Pieter Abbeel, and Mariano Phielipp · 2019
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Self-supervised learning of image embedding for continuous control
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Using natural language for reward shaping in reinforcement learning, 2019
Prasoon Goyal, Scott Niekum, and Raymond J. Mooney · 2019
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Mapping instructions and visual observations to actions with reinforcement learning
Dipendra Misra, John Langford, and Yoav Artzi · 2017
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Zero-shot task generalization with multi-task deep reinforcement learning
Junhyuk Oh, Satinder Singh, Honglak Lee, and Pushmeet Kohli · 2017
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Learning complex dexterous manipulation with deep reinforcement learning and demonstrations
Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, Giulia Vezzani, John Schulman, Emanuel Todorov, and Sergey Levine · 2017
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Distral: Robust multitask reinforcement learning
Yee Teh, Victor Bapst, Wojciech M Czarnecki, John Quan, James Kirkpatrick, Raia Hadsell, Nicolas Heess, and Razvan Pascanu · 2017
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Babyai: A platform to study the sample efficiency of grounded language learning
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Visual foresight: Model-based deep reinforcement learning for vision-based robotic control
Frederik Ebert, Chelsea Finn, Sudeep Dasari, Annie Xie, Alex Lee, and Sergey Levine · 2018
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Felix Hill, Andrew Lampinen, Rosalia Schneider, Stephen Clark, Matthew Botvinick, James L McClelland, and Adam Santoro · 2019
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Language as an abstraction for hierarchical deep reinforcement learning, 2019
Yiding Jiang, Shixiang Gu, Kevin Murphy, and Chelsea Finn · 2019
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A survey of reinforcement learning informed by natural language
Jelena Luketina, Nantas Nardelli, Gregory Farquhar, Jakob Foerster, Jacob Andreas, Edward Grefenstette, Shimon Whiteson, and Tim Rocktäschel · 2019
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Wasserstein dependency measure for representation learning
Sherjil Ozair, Corey Lynch, Yoshua Bengio, Aaron Van den Oord, Sergey Levine, and Pierre Sermanet · 2019
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Online object representations with contrastive learning
Sören Pirk, Mohi Khansari, Yunfei Bai, Corey Lynch, and Pierre Sermanet · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
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End-to-end robotic reinforcement learning without reward engineering
Avi Singh, Larry Yang, Kristian Hartikainen, Chelsea Finn, and Sergey Levine · 2019
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Reinforced cross-modal matching and self-supervised imitation learning for vision-language navigation
Xin Wang, Qiuyuan Huang, Asli Celikyilmaz, Jianfeng Gao, Dinghan Shen, Yuan-Fang Wang, William Yang Wang, and Lei Zhang · 2019
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Multilingual universal sentence encoder for semantic retrieval
Yinfei Yang, Daniel Cer, Amin Ahmad, Mandy Guo, Jax Law, Noah Constant, Gustavo Hernandez Abrego, Steve Yuan, Chris Tar, Yun-Hsuan Sung, et al · 2019
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Rtfm: Generalising to novel environment dynamics via reading
Victor Zhong, Tim Rocktäschel, and Edward Grefenstette · 2019
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Contextual imagined goals for self-supervised robotic learning
Ashvin Nair, Shikhar Bahl, Alexander Khazatsky, Vitchyr Pong, Glen Berseth, and Sergey Levine · 2020
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Scalable multi-task imitation learning with autonomous improvement
Avi Singh, Eric Jang, Alexander Irpan, Daniel Kappler, Murtaza Dalal, Sergey Levine, Mohi Khansari, and Chelsea Finn · 2020
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Language-conditioned imitation learning for robot manipulation tasks
Simon Stepputtis, Joseph Campbell, Mariano Phielipp, Stefan Lee, Chitta Baral, and Heni Ben Amor · 2020
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