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Humans learn to master open-ended repertoires of skills by imagining and practicing their own goals.
Words as invitations to form categories: Evidence from 12-to 13-month-old infants
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Syntactic structures
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Pierre-Yves Oudeyer and Frederic Kaplan · 2007
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Claudio Tennie, Josep Call, and Michael Tomasello · 2009
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Intrinsically motivated reinforcement learning: An evolutionary perspective
Satinder Singh, Richard L Lewis, Andrew G Barto, and Jonathan Sorg · 2010
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Powerplay: Training an increasingly general problem solver by continually searching for the simplest still unsolvable problem
Jürgen Schmidhuber · 2013
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Language understanding for text-based games using deep reinforcement learning
Karthik Narasimhan, Tejas Kulkarni, and Regina Barzilay · 2015
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Universal value function approximators
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Deep reinforcement learning with a natural language action space
Ji He, Jianshu Chen, Xiaodong He, Jianfeng Gao, Lihong Li, Li Deng, and Mari Ostendorf · 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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Language as a disruptive technology: abstract concepts, embodiment and the flexible mind
Guy Dove · 2018
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Rainbow: Combining improvements in deep reinforcement learning
Matteo Hessel, Joseph Modayil, Hado Van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Dan Horgan, Bilal Piot, Mohammad Azar, and David Silver · 2018
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Unsupervised control through non-parametric discriminative rewards
David Warde-Farley, Tom Van de Wiele, Tejas Kulkarni, Catalin Ionescu, Steven Hansen, and Volodymyr Mnih · 2018
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A survey on intrinsic motivation in reinforcement learning
Arthur Aubret, Laetitia Matignon, and Salima Hassas · 2019
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Curious: intrinsically motivated modular multi-goal reinforcement learning
Cédric Colas, Pierre Fournier, Mohamed Chetouani, Olivier Sigaud, and Pierre-Yves Oudeyer · 2019
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Textworld: A learning environment for text-based games
Marc-Alexandre Côté, Akos Kádár, Xingdi Yuan, Ben Kybartas, Tavian Barnes, Emery Fine, James Moore, Matthew Hausknecht, Layla El Asri, Mahmoud Adada, et al · 2019
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Diversity is all you need: Learning skills without a reward function
Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, and Sergey Levine · 2019
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Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych · 2019
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First return, then explore
Adrien Ecoffet, Joost Huizinga, Joel Lehman, Kenneth O Stanley, and Jeff Clune · 2021
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Reinforcement learning as one big sequence modeling problem
Michael Janner, Qiyang Li, and Sergey Levine · 2021
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Prioritized level replay
Minqi Jiang, Edward Grefenstette, and Tim Rocktäschel · 2021
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Do as i can, not as i say: Grounding language in robotic affordances
Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alex Herzog, et al · 2022
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Minedojo: Building open-ended embodied agents with internet-scale knowledge
Linxi Fan, Guanzhi Wang, Yunfan Jiang, Ajay Mandlekar, Yuncong Yang, Haoyi Zhu, Andrew Tang, De-An Huang, Yuke Zhu, and Anima Anandkumar · 2022
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Play, curiosity, and cognition
Junyi Chu and Laura E Schulz · 2020
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Language as a cognitive tool to imagine goals in curiosity driven exploration
Cédric Colas, Tristan Karch, Nicolas Lair, Jean-Michel Dussoux, Clément Moulin-Frier, Peter Dominey, and Pierre-Yves Oudeyer · 2020
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Adapting behavior via intrinsic reward: A survey and empirical study
Cam Linke, Nadia M Ady, Martha White, Thomas Degris, and Adam White · 2020
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Language conditioned imitation learning over unstructured data
Corey Lynch and Pierre Sermanet · 2020
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Exploration based language learning for text-based games
Andrea Madotto, Mahdi Namazifar, Joost Huizinga, Piero Molino, Adrien Ecoffet, Huaixiu Zheng, Alexandros Papangelis, Dian Yu, Chandra Khatri, and Gokhan Tur · 2020
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Skew-fit: State-covering self-supervised reinforcement learning
Vitchyr Pong, Murtaza Dalal, Steven Lin, Ashvin Nair, Shikhar Bahl, and Sergey Levine · 2020
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Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2022
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Code as policies: Language model programs for embodied control
Jacky Liang, Wenlong Huang, Fei Xia, Peng Xu, Karol Hausman, Brian Ichter, Pete Florence, and Andy Zeng · 2022
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Progprompt: Generating situated robot task plans using large language models
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Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, brian ichter, Fei Xia, Ed H. Chi, Quoc V Le, and Denny Zhou · 2022
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Robotic skill acquisition via instruction augmentation with vision-language models
Ted Xiao, Harris Chan, Pierre Sermanet, Ayzaan Wahid, Anthony Brohan, Karol Hausman, Sergey Levine, and Jonathan Tompson · 2022
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Grounding large language models in interactive environments with online reinforcement learning
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Large language models can segment narrative events similarly to humans
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Human-timescale adaptation in an open-ended task space
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