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Autonomous agents have made great strides in specialist domains like Atari games and Go.
The minerl 2019 competition on sample efficient reinforcement learning using human priors
William H. Guss, Cayden Codel, Katja Hofmann, Brandon Houghton, Noboru Kuno, Stephanie Milani, Sharada Mohanty, Diego Perez Liebana, Ruslan Salakhutdinov, Nicholay Topin, Manuela Veloso, and Phillip Wang · 1904
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Minerl: A large-scale dataset of minecraft demonstrations
William H. Guss, Brandon Houghton, Nicholay Topin, Phillip Wang, Cayden Codel, Manuela Veloso, and Ruslan Salakhutdinov · 1907
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Open-ended artificial evolution
Russell K Standish · 2003
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Pfeiffer–a distributed open-ended evolutionary system
WB Langdon · 2005
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Objectnav revisited: On evaluation of embodied agents navigating to objects
Dhruv Batra, Aaron Gokaslan, Aniruddha Kembhavi, Oleksandr Maksymets, Roozbeh Mottaghi, Manolis Savva, Alexander Toshev, and Erik Wijmans · 2006
Earlier work this paper cites.
Rearrangement: A challenge for embodied ai
Dhruv Batra, Angel X. Chang, Sonia Chernova, Andrew J. Davison, Jia Deng, Vladlen Koltun, Sergey Levine, Jitendra Malik, Igor Mordatch, Roozbeh Mottaghi, Manolis Savva, and Hao Su · 2011
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Playing atari with deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller · 2013
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Youtube-8m: A large-scale video classification benchmark
Sami Abu-El-Haija, Nisarg Kothari, Joonseok Lee, Paul Natsev, George Toderici, Balakrishnan Varadarajan, and Sudheendra Vijayanarasimhan · 2016
Earlier work this paper cites.
Conversational contextual cues: The case of personalization and history for response ranking
Rami Al-Rfou, Marc Pickett, Javier Snaider, Yun hsuan Sung, Brian Strope, and Ray Kurzweil · 2016
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Openai gym
Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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The malmo platform for artificial intelligence experimentation
Matthew Johnson, Katja Hofmann, Tim Hutton, and David Bignell · 2016
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Improved techniques for training gans
Tim Salimans, Ian J. Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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High-dimensional continuous control using generalized advantage estimation
John Schulman, Philipp Moritz, Sergey Levine, Michael I. Jordan, and Pieter Abbeel · 2016
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Open-ended evolution: Perspectives from the oee workshop in york
Tim Taylor, Mark Bedau, Alastair Channon, David Ackley, Wolfgang Banzhaf, Guillaume Beslon, Emily Dolson, Tom Froese, Simon Hickinbotham, Takashi Ikegami, et al · 2016
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Modular multitask reinforcement learning with policy sketches
Jacob Andreas, Dan Klein, and Sergey Levine · 2017
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Quo vadis, action recognition? A new model and the kinetics dataset
João Carreira and Andrew Zisserman · 2017
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The" something something" video database for learning and evaluating visual common sense
Raghav Goyal, Samira Ebrahimi Kahou, Vincent Michalski, Joanna Materzynska, Susanne Westphal, Heuna Kim, Valentin Haenel, Ingo Fruend, Peter Yianilos, Moritz Mueller-Freitag, et al · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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The kinetics human action video dataset
Will Kay, Joao Carreira, Karen Simonyan, Brian Zhang, Chloe Hillier, Sudheendra Vijayanarasimhan, Fabio Viola, Tim Green, Trevor Back, Paul Natsev, Mustafa Suleyman, and Andrew Zisserman · 2017
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Ai2-thor: An interactive 3d environment for visual ai
Eric Kolve, Roozbeh Mottaghi, Winson Han, Eli VanderBilt, Luca Weihs, Alvaro Herrasti, Daniel Gordon, Yuke Zhu, Abhinav Gupta, and Ali Farhadi · 2017
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SGDR: stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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World of bits: an open-domain platform for web-based agents
Tianlin Tim Shi, Andrej Karpathy, Linxi Jim Fan, Jonathan Hernandez, and Percy Liang · 2017
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Mastering chess and shogi by self-play with a general reinforcement learning algorithm
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy Lillicrap, Karen Simonyan, and Demis Hassabis · 2017
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Third-person imitation learning
Bradly C. Stadie, Pieter Abbeel, and Ilya Sutskever · 2017
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Open-endedness: The last grand challenge you’ve never heard of
Kenneth O Stanley, Joel Lehman, and Lisa Soros · 2017
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TL;DR: Mining Reddit to learn automatic summarization
Michael Vølske, Martin Potthast, Shahbaz Syed, and Benno Stein · 2017
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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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Imitating latent policies from observation
Ashley D. Edwards, Himanshu Sahni, Yannick Schroecker, and Charles L. Isbell · 2018
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Mixed precision training
Paulius Micikevicius, Sharan Narang, Jonah Alben, Gregory F. Diamos, Erich Elsen, David García, Boris Ginsburg, Michael Houston, Oleksii Kuchaiev, Ganesh Venkatesh, and Hao Wu · 2018
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Self-imitation learning
Junhyuk Oh, Yijie Guo, Satinder Singh, and Honglak Lee · 2018
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Virtualhome: Simulating household activities via programs
Xavier Puig, Kevin Ra, Marko Boben, Jiaman Li, Tingwu Wang, Sanja Fidler, and Antonio Torralba · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
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Deepmind control suite
Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, Timothy Lillicrap, and Martin Riedmiller · 2018
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Behavioral cloning from observation
Faraz Torabi, Garrett Warnell, and Peter Stone · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Rethinking spatiotemporal feature learning: Speed-accuracy trade-offs in video classification
Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu, and Kevin Murphy · 2018
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Learning semantic textual similarity from conversations
Yinfei Yang, Steve Yuan, Daniel Cer, Sheng-yi Kong, Noah Constant, Petr Pilar, Heming Ge, Yun-Hsuan Sung, Brian Strope, and Ray Kurzweil · 2018
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Babyai: A platform to study the sample efficiency of grounded language learning
Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, Lucas Willems, Chitwan Saharia, Thien Huu Nguyen, and Yoshua Bengio · 2019
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Robonet: Large-scale multi-robot learning
Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, and Chelsea Finn · 2019
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Go-explore: a new approach for hard-exploration problems
Adrien Ecoffet, Joost Huizinga, Joel Lehman, Kenneth O. Stanley, and Jeff Clune · 2019
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PyTorch Lightning
William Falcon and The PyTorch Lightning team · 2019
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Craftassist: A framework for dialogue-enabled interactive agents
Jonathan Gray, Kavya Srinet, Yacine Jernite, Haonan Yu, Zhuoyuan Chen, Demi Guo, Siddharth Goyal, C. Lawrence Zitnick, and Arthur Szlam · 2019
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A repository of conversational datasets
Matthew Henderson, Paweł Budzianowski, Iñigo Casanueva, Sam Coope, Daniela Gerz, Girish Kumar, Nikola Mrkšić, Georgios Spithourakis, Pei-Hao Su, Ivan Vulić, and Tsung-Hsien Wen · 2019
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Obstacle tower: A generalization challenge in vision, control, and planning
Arthur Juliani, Ahmed Khalifa, Vincent-Pierre Berges, Jonathan Harper, Ervin Teng, Hunter Henry, Adam Crespi, Julian Togelius, and Danny Lange · 2019
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Abstractive summarization of reddit posts with multi-level memory networks
Byeongchang Kim, Hyunwoo Kim, and Gunhee Kim · 2019
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Howto100m: Learning a text-video embedding by watching hundred million narrated video clips
Antoine Miech, Dimitri Zhukov, Jean-Baptiste Alayrac, Makarand Tapaswi, Ivan Laptev, and Josef Sivic · 2019
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Dota 2 with large scale deep reinforcement learning
OpenAI, :, Christopher Berner, Greg Brockman, Brooke Chan, Vicki Cheung, Przemysław Dębiak, Christy Dennison, David Farhi, Quirin Fischer, Shariq Hashme, Chris Hesse, Rafal Józefowicz, Scott Gray, Catherine Olsson, Jakub Pachocki, Michael Petrov, Henrique P. d. O. Pinto, Jonathan Raiman, Tim Salimans, Jeremy Schlatter, Jonas Schneider, Szymon Sidor, Ilya Sutskever, Jie Tang, Filip Wolski, and Susan Zhang · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
Cited alongside, same era.
The multi-agent reinforcement learning in malmÖ (marlÖ) competition
Diego Perez-Liebana, Katja Hofmann, Sharada Prasanna Mohanty, Noburu Kuno, Andre Kramer, Sam Devlin, Raluca D. Gaina, and Daniel Ionita · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Cited alongside, same era.
Habitat: A platform for embodied ai research
Manolis Savva, Abhishek Kadian, Oleksandr Maksymets, Yili Zhao, Erik Wijmans, Bhavana Jain, Julian Straub, Jia Liu, Vladlen Koltun, Jitendra Malik, Devi Parikh, and Dhruv Batra · 2019
Cited alongside, same era.
Megatron-lm: Training multi-billion parameter language models using model parallelism
Minecraft, the most-watched game on youtube, passes 1 trillion views, Dec 2021
Jordan Gerblick · 2021
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EvoCraft: A New Challenge for Open-Endedness , pages 325–340
Djordje Grbic, Rasmus Berg Palm, Elias Najarro, Claire Glanois, and Sebastian Risi · 2021
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The minerl 2020 competition on sample efficient reinforcement learning using human priors
William H. Guss, Mario Ynocente Castro, Sam Devlin, Brandon Houghton, Noboru Sean Kuno, Crissman Loomis, Stephanie Milani, Sharada Mohanty, Keisuke Nakata, Ruslan Salakhutdinov, John Schulman, Shinya Shiroshita, Nicholay Topin, Avinash Ummadisingu, and Oriol Vinyals · 2021
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Benchmarking the spectrum of agent capabilities
Danijar Hafner · 2021
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Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2021
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Mohammad Shoeybi, Mostofa Patwary, Raul Puri, Patrick LeGresley, Jared Casper, and Bryan Catanzaro · 2019
Cited alongside, same era.
Avid: Learning multi-stage tasks via pixel-level translation of human videos
Laura Smith, Nikita Dhawan, Marvin Zhang, Pieter Abbeel, and Sergey Levine · 2019
Cited alongside, same era.
Learning video representations using contrastive bidirectional transformer
Chen Sun, Fabien Baradel, Kevin Murphy, and Cordelia Schmid · 2019
Cited alongside, same era.
Recent advances in imitation learning from observation
Faraz Torabi, Garrett Warnell, and Peter Stone · 2019
Cited alongside, same era.
Alphastar: Mastering the real-time strategy game starcraft ii
Oriol Vinyals, Igor Babuschkin, Junyoung Chung, Michael Mathieu, Max Jaderberg, Wojciech M Czarnecki, Andrew Dudzik, Aja Huang, Petko Georgiev, Richard Powell, et al · 2019
Cited alongside, same era.
Paired open-ended trailblazer (poet): Endlessly generating increasingly complex and diverse learning environments and their solutions
Rui Wang, Joel Lehman, Jeff Clune, and Kenneth O. Stanley · 2019
Cited alongside, same era.
Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush · 2019
Cited alongside, same era.
Interactive gibson benchmark (igibson 0.5): A benchmark for interactive navigation in cluttered environments
Fei Xia, William B. Shen, Chengshu Li, Priya Kasimbeg, Micael Tchapmi, Alexander Toshev, Li Fei-Fei, Roberto Martín-Martín, and Silvio Savarese · 2019
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Michael Janner, Qiyang Li, and Sergey Levine · 2021
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Multi-task curriculum learning in a complex, visual, hard-exploration domain: Minecraft
Ingmar Kanitscheider, Joost Huizinga, David Farhi, William Hebgen Guss, Brandon Houghton, Raul Sampedro, Peter Zhokhov, Bowen Baker, Adrien Ecoffet, Jie Tang, Oleg Klimov, and Jeff Clune · 2021
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Neurips 2021 competition iglu: Interactive grounded language understanding in a collaborative environment
Julia Kiseleva, Ziming Li, Mohammad Aliannejadi, Shrestha Mohanty, Maartje ter Hoeve, Mikhail Burtsev, Alexey Skrynnik, Artem Zholus, Aleksandr Panov, Kavya Srinet, Arthur Szlam, Yuxuan Sun, Katja Hofmann, Michel Galley, and Ahmed Awadallah · 2021
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Clip4clip: An empirical study of clip for end to end video clip retrieval
Huaishao Luo, Lei Ji, Ming Zhong, Yang Chen, Wen Lei, Nan Duan, and Tianrui Li · 2021
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Learning language-conditioned robot behavior from offline data and crowd-sourced annotation
Suraj Nair, Eric Mitchell, Kevin Chen, Brian Ichter, Silvio Savarese, and Chelsea Finn · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Laion-400m: Open dataset of clip-filtered 400 million image-text pairs
Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, and Aran Komatsuzaki · 2021
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The minerl basalt competition on learning from human feedback
Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William Guss, Sharada Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, Pieter Abbeel, Stuart Russell, and Anca Dragan · 2021
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Concept2robot: Learning manipulation concepts from instructions and human demonstrations
Lin Shao, Toki Migimatsu, Qiang Zhang, Karen Yang, and Jeannette Bohg · 2021
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Cliport: What and where pathways for robotic manipulation
Mohit Shridhar, Lucas Manuelli, and Dieter Fox · 2021
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BEHAVIOR: benchmark for everyday household activities in virtual, interactive, and ecological environments
Sanjana Srivastava, Chengshu Li, Michael Lingelbach, Roberto Martín-Martín, Fei Xia, Kent Elliott Vainio, Zheng Lian, Cem Gokmen, Shyamal Buch, C. Karen Liu, Silvio Savarese, Hyowon Gweon, Jiajun Wu, and Li Fei-Fei · 2021
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Open-ended learning leads to generally capable agents
Open Ended Learning Team, Adam Stooke, Anuj Mahajan, Catarina Barros, Charlie Deck, Jakob Bauer, Jakub Sygnowski, Maja Trebacz, Max Jaderberg, Michael Mathieu, Nat McAleese, Nathalie Bradley-Schmieg, Nathaniel Wong, Nicolas Porcel, Roberta Raileanu, Steph Hughes-Fitt, Valentin Dalibard, and Wojciech Marian Czarnecki · 2021
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Androidenv: A reinforcement learning platform for android
Daniel Toyama, Philippe Hamel, Anita Gergely, Gheorghe Comanici, Amelia Glaese, Zafarali Ahmed, Tyler Jackson, Shibl Mourad, and Doina Precup · 2021
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Videoclip: Contrastive pre-training for zero-shot video-text understanding
Hu Xu, Gargi Ghosh, Po-Yao Huang, Dmytro Okhonko, Armen Aghajanyan, Florian Metze, Luke Zettlemoyer, and Christoph Feichtenhofer · 2021
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Xirl: Cross-embodiment inverse reinforcement learning
Kevin Zakka, Andy Zeng, Pete Florence, Jonathan Tompson, Jeannette Bohg, and Debidatta Dwibedi · 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, Daniel Ho, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Eric Jang, Rosario Jauregui Ruano, Kyle Jeffrey, Sally Jesmonth, Nikhil J Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Kuang-Huei Lee, Sergey Levine, Yao Lu, Linda Luu, Carolina Parada, Peter Pastor, Jornell Quiambao, Kanishka Rao, Jarek Rettinghouse, Diego Reyes, Pierre Sermanet, Nicolas Sievers, Clayton Tan, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, and Mengyuan Yan · 2022
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Video pretraining (vpt): Learning to act by watching unlabeled online videos
Bowen Baker, Ilge Akkaya, Peter Zhokhov, Joost Huizinga, Jie Tang, Adrien Ecoffet, Brandon Houghton, Raul Sampedro, and Jeff Clune · 2022
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Common crawl
Common Crawl · 2022
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A survey of embodied AI: from simulators to research tasks
Jiafei Duan, Samson Yu, Hui Li Tan, Hongyuan Zhu, and Cheston Tan · 2022
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Metamorph: Learning universal controllers with transformers
Agrim Gupta, Linxi Fan, Surya Ganguli, and Li Fei-Fei · 2022
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Inner monologue: Embodied reasoning through planning with language models
Wenlong Huang, Fei Xia, Ted Xiao, Harris Chan, Jacky Liang, Pete Florence, Andy Zeng, Jonathan Tompson, Igor Mordatch, Yevgen Chebotar, Pierre Sermanet, Noah Brown, Tomas Jackson, Linda Luu, Sergey Levine, Karol Hausman, and Brian Ichter · 2022
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Evolving multimodal robot behavior via many stepping stones with the combinatorial multiobjective evolutionary algorithm
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Minerl diamond 2021 competition: Overview, results, and lessons learned
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Large language models are zero-shot reasoners
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Label Studio · 2022
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The primacy bias in deep reinforcement learning
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PRAW: The Python Reddit API Wrapper · 2022
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Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, and Nando de Freitas · 2022
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