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Learning policies from previously recorded data is a promising direction for real-world robotics tasks, as online learning is often infeasible.
Ashish Kumar, Toby Buckley, John B Lanier, Qiaozhi Wang, Alicia Kavelaars, and Ilya Kuzovkin · 1910
Earlier work this paper cites.
AlgaeDICE: Policy gradient from arbitrary experience
Ofir Nachum, Bo Dai, Ilya Kostrikov, Yinlam Chow, Lihong Li, and Dale Schuurmans · 1912
Earlier work this paper cites.
Efficient training of artificial neural networks for autonomous navigation
Dean A Pomerleau · 1991
Earlier work this paper cites.
A framework for behavioural cloning
Michael Bain and Claude Sammut · 1995
Earlier work this paper cites.
Reinforcement Learning: An Introduction
Richard S Sutton, Andrew G Barto, and Co-Director Autonomous Learning Laboratory Andrew G Barto · 1998
Earlier work this paper cites.
Robot competitions-ideal benchmarks for robotics research
Sven Behnke · 2006
Earlier work this paper cites.
A reduction of imitation learning and structured prediction to no-regret online learning
Stéphane Ross, Geoffrey J. Gordon, and Drew Bagnell · 2011
Earlier work this paper cites.
ImageNet Classification with Deep Convolutional Neural Networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
Earlier work this paper cites.
Batch reinforcement learning
Sascha Lange, Thomas Gabel, and Martin Riedmiller · 2012
Earlier work this paper cites.
Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
Earlier work this paper cites.
Competitions for benchmarking: Task and functionality scoring complete performance assessment
Francesco Amigoni, Emanuele Bastianelli, Jakob Berghofer, Andrea Bonarini, Giulio Fontana, Nico Hochgeschwender, Luca Iocchi, Gerhard Kraetzschmar, Pedro Lima, Matteo Matteucci, Pedro Miraldo, Daniele Nardi, and Viola Schiaffonati · 2015
Earlier work this paper cites.
Toward replicable and measurable robotics research [from the guest editors]
Fabio Bonsignorio and Angel P. del Pobil · 2015
Earlier work this paper cites.
Benchmarking in Manipulation Research: The YCB Object and Model Set and Benchmarking Protocols
Berk Calli, Aaron Walsman, Arjun Singh, Siddhartha Srinivasa, Pieter Abbeel, and Aaron M Dollar · 2015
Earlier work this paper cites.
Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, and Demis Hassabis · 2015
Earlier work this paper cites.
Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
Earlier work this paper cites.
Pybullet, a python module for physics simulation for games, robotics and machine learning
Erwin Coumans and Yunfei Bai · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Continuous control with deep reinforcement learning
Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra · 2016
Earlier work this paper cites.
You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
Earlier work this paper cites.
Adversarially robust policy learning through active construction of physically-plausible perturbations
Ajay Mandlekar, Yuke Zhu, Animesh Garg, Li Fei-Fei, and Silvio Savarese · 2017
Earlier work this paper cites.
Duckietown: an open, inexpensive and flexible platform for autonomy education and research
Liam Paull, Jacopo Tani, Heejin Ahn, Javier Alonso-Mora, Luca Carlone, Michal Cap, Yu Fan Chen, Changhyun Choi, Jeff Dusek, Yajun Fang, et al · 2017
Earlier work this paper cites.
The robotarium: A remotely accessible swarm robotics research testbed
Daniel Pickem, Paul Glotfelter, Li Wang, Mark Mote, Aaron Ames, Eric Feron, and Magnus Egerstedt · 2017
Earlier work this paper cites.
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
Earlier work this paper cites.
Mastering the game of go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, et al · 2017
Earlier work this paper cites.
Domain randomization for transferring deep neural networks from simulation to the real world
Josh Tobin, Rachel Fong, Alex Ray, Jonas Schneider, Wojciech Zaremba, and Pieter Abbeel · 2017
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Earlier work this paper cites.
Learning Dexterous In-Hand Manipulation
OpenAI, Marcin Andrychowicz, Bowen Baker, Maciek Chociej, Rafal Jozefowicz, Bob McGrew, Jakub Pachocki, Arthur Petron, Matthias Plappert, Glenn Powell, Alex Ray, Jonas Schneider, Szymon Sidor, Josh Tobin, Peter Welinder, Lilian Weng, and Wojciech Zaremba · 2018
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Time limits in reinforcement learning
Fabio Pardo, Arash Tavakoli, Vitaly Levdik, and Petar Kormushev · 2018
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Sim-to-real transfer of robotic control with dynamics randomization
Xue Bin Peng, Marcin Andrychowicz, Wojciech Zaremba, and Pieter Abbeel · 2018
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Behavioral cloning from observation
Faraz Torabi, Garrett Warnell, and Peter Stone · 2018
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Dota 2 with large scale deep reinforcement learning
Christopher Berner, Greg Brockman, Brooke Chan, Vicki Cheung, Przemysław Dębiak, Christy Dennison, David Farhi, Quirin Fischer, Shariq Hashme, Chris Hesse, et al · 2019
Accelerating online reinforcement learning with offline datasets
Ashvin Nair, Murtaza Dalal, Abhishek Gupta, and Sergey Levine · 2020
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Critic regularized regression
Ziyu Wang, Alexander Novikov, Konrad Zolna, Josh Merel, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Çaglar Gülçehre, Nicolas Heess, and Nando de Freitas · 2020
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GenDICE: Generalized offline estimation of stationary values
Ruiyi Zhang, Bo Dai, Lihong Li, and Dale Schuurmans · 2020
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Real robot challenge: A robotics competition in the cloud
Stefan Bauer, Manuel Wüthrich, Felix Widmaier, Annika Buchholz, Sebastian Stark, Anirudh Goyal, Thomas Steinbrenner, Joel Akpo, Shruti Joshi, Vincent Berenz, Vaibhav Agrawal, Niklas Funk, Julen Urain De Jesus, Jan Peters, Joe Watson, Claire Chen, Krishnan Srinivasan, Junwu Zhang, Jeffrey Zhang, Matthew Walter, Rishabh Madan, Takuma Yoneda, Denis Yarats, Arthur Allshire, Ethan Gordon, Tapomayukh Bhattacharjee, Siddhartha Srinivasa, Animesh Garg, Takahiro Maeda, Harshit Sikchi, Jilong Wang, Qingfeng Yao, Shuyu Yang, Robert McCarthy, Francisco Sanchez, Qiang Wang, David Bulens, Kevin McGuinness, Noel O’Connor, Redmond Stephen, and Bernhard Schölkopf · 2021
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Off-policy deep reinforcement learning without exploration
Scott Fujimoto, David Meger, and Doina Precup · 2019
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Learning agile and dynamic motor skills for legged robots
Jemin Hwangbo, Joonho Lee, Alexey Dosovitskiy, Dario Bellicoso, Vassilios Tsounis, Vladlen Koltun, and Marco Hutter · 2019
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When to trust your model: Model-based policy optimization
Michael Janner, Justin Fu, Marvin Zhang, and Sergey Levine · 2019
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Stabilizing off-policy q-learning via bootstrapping error reduction
Aviral Kumar, Justin Fu, Matthew Soh, George Tucker, and Sergey Levine · 2019
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PyRobot: An Open-source Robotics Framework for Research and Benchmarking
Adithyavairavan Murali, Tao Chen, Kalyan Vasudev Alwala, Dhiraj Gandhi, Lerrel Pinto, Saurabh Gupta, and Abhinav Gupta · 2019
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DualDICE: Behavior-agnostic estimation of discounted stationary distribution corrections
Ofir Nachum, Yinlam Chow, Bo Dai, and Lihong Li · 2019
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Solving Rubik’s Cube with a Robot Hand
OpenAI, Ilge Akkaya, Marcin Andrychowicz, Maciek Chociej, Mateusz Litwin, Bob McGrew, Arthur Petron, Alex Paino, Matthias Plappert, Glenn Powell, Raphael Ribas, Jonas Schneider, Nikolas Tezak, Jerry Tworek, Peter Welinder, Lilian Weng, Qiming Yuan, Wojciech Zaremba, and Lei Zhang · 2019
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Offline RL without off-policy evaluation
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Decision transformer: Reinforcement learning via sequence modeling
Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Misha Laskin, Pieter Abbeel, Aravind Srinivas, and Igor Mordatch · 2021
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Brax - a differentiable physics engine for large scale rigid body simulation, 2021
C. Daniel Freeman, Erik Frey, Anton Raichuk, Sertan Girgin, Igor Mordatch, and Olivier Bachem · 2021
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A minimalist approach to offline reinforcement learning
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Offline reinforcement learning as one big sequence modeling problem
Michael Janner, Qiyang Li, and Sergey Levine · 2021
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Offline reinforcement learning with fisher divergence critic regularization
Ilya Kostrikov, Rob Fergus, Jonathan Tompson, and Ofir Nachum · 2021
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A workflow for offline model-free robotic reinforcement learning
Aviral Kumar, Anikait Singh, Stephen Tian, Chelsea Finn, and Sergey Levine · 2021
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Isaac gym: High performance gpu-based physics simulation for robot learning
Viktor Makoviychuk, Lukasz Wawrzyniak, Yunrong Guo, Michelle Lu, Kier Storey, Miles Macklin, David Hoeller, Nikita Rudin, Arthur Allshire, Ankur Handa, et al · 2021
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What matters in learning from offline human demonstrations for robot manipulation
Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, and Roberto Martín-Martín · 2021
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Regularizing action policies for smooth control with reinforcement learning
Siddharth Mysore, Bassel Mabsout, Renato Mancuso, and Kate Saenko · 2021
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d3rlpy: An offline deep reinforcement learning library
Takuma Seno and Michita Imai · 2021
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Trifinger: An open-source robot for learning dexterity
Manuel Wüthrich, Felix Widmaier, Felix Grimminger, Shruti Joshi, Vaibhav Agrawal, Bilal Hammoud, Majid Khadiv, Miroslav Bogdanovic, Vincent Berenz, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Bernhard Schölkopf, and Stefan Bauer · 2021
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Offline reinforcement learning with soft behavior regularization
Haoran Xu, Xianyuan Zhan, Jianxiong Li, and Honglei Yin · 2021
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COMBO: conservative offline model-based policy optimization
Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, and Chelsea Finn · 2021
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BRAC+: improved behavior regularized actor critic for offline reinforcement learning
Chi Zhang, Sanmukh R. Kuppannagari, and Viktor K. Prasanna · 2021
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The ai driving olympics (ai-do)
AI-DO-team · 2022
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Transferring dexterous manipulation from GPU simulation to a remote real-world trifinger
Arthur Allshire, Mayank MittaI, Varun Lodaya, Viktor Makoviychuk, Denys Makoviichuk, Felix Widmaier, Manuel Wüthrich, Stefan Bauer, Ankur Handa, and Animesh Garg · 2022
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Adversarially trained actor critic for offline reinforcement learning
Ching-An Cheng, Tengyang Xie, Nan Jiang, and Alekh Agarwal · 2022
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rl-games: A high-performance framework for reinforcement learning
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A survey on offline reinforcement learning: Taxonomy, review, and open problems
Rafael Figueiredo Prudencio, Marcos R. O. A. Maximo, and Esther Luna Colombini · 2022
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Dexterous robotic manipulation using deep reinforcement learning and knowledge transfer for complex sparse reward-based tasks
Qiang Wang, Francisco Roldan Sanchez, Robert McCarthy, David Cordova Bulens, Kevin McGuinness, Noel O’Connor, Manuel Wüthrich, Felix Widmaier, Stefan Bauer, and Stephen J. Redmond · 2022
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