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We present a deep imitation learning framework for robotic bimanual manipulation in a continuous state-action space.
Learning from demonstration
Stefan Schaal · 1997
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Between mdps and semi-mdps: A framework for temporal abstraction in reinforcement learning
Richard S Sutton, Doina Precup, and Satinder Singh · 1999
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The graph neural network model
Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini · 2008
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Learning and generalization of motor skills by learning from demonstration
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A survey of robot learning from demonstration
Brenna D. Argall, Sonia Chernova, Manuela Veloso, and Brett Browning · 2009
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Learning and generalization of motor skills by learning from demonstration
Peter Pastor, Heiko Hoffmann, Tamim Asfour, and Stefan Schaal · 2009
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Dual arm manipulation—a survey
Christian Smith, Yiannis Karayiannidis, Lazaros Nalpantidis, Xavi Gratal, Peng Qi, Dimos V Dimarogonas, and Danica Kragic · 2012
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Bruno Da Silva, George Konidaris, and Andrew Barto · 2012
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Milos Hauskrecht, Nicolas Meuleau, Leslie Pack Kaelbling, Thomas L Dean, and Craig Boutilier · 2013
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Diederik P Kingma and Max Welling · 2013
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Ilya Sutskever, Oriol Vinyals, and Quoc V Le · 2014
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On the properties of neural machine translation: Encoder-decoder approaches, 2014
Kyunghyun Cho, Bart van Merrienboer, Dzmitry Bahdanau, and Yoshua Bengio · 2014
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Towards learning hierarchical skills for multi-phase manipulation tasks
Oliver Kroemer, Christian Daniel, Gerhard Neumann, Herke Van Hoof, and Jan Peters · 2015
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Learning movement primitive attractor goals and sequential skills from kinesthetic demonstrations
Simon Manschitz, Jens Kober, Michael Gienger, and Jan Peters · 2015
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Reinforcement learning with parameterized actions
Warwick Masson, Pravesh Ranchod, and George Konidaris · 2016
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Deep reinforcement learning in parameterized action space
Matthew J. Hausknecht and Peter Stone · 2016
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Ddco: Discovery of deep continuous options for robot learning from demonstrations, 2017
Sanjay Krishnan, Roy Fox, Ion Stoica, and Ken Goldberg · 2017
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Learning deep movement primitives using convolutional neural networks
A. Pervez, Y. Mao, and D. Lee · 2017
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Learning mobile manipulation actions from human demonstrations
T. Welschehold, C. Dornhege, and W. Burgard · 2017
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One-shot visual imitation learning via meta-learning
Chelsea Finn, Tianhe Yu, Tianhao Zhang, Pieter Abbeel, and Sergey Levine · 2017
Hierarchical imitation and reinforcement learning
Hoang M Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue, and Hal Daumé · 2018
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Neural relational inference for interacting systems
Thomas Kipf, Ethan Fetaya, Kuan-Chieh Wang, Max Welling, and Richard Zemel · 2018
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Flexible neural representation for physics prediction
Damian Mrowca, Chengxu Zhuang, Elias Wang, Nick Haber, Li F Fei-Fei, Josh Tenenbaum, and Daniel L Yamins · 2018
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Object-oriented dynamics predictor
Guangxiang Zhu, Zhiao Huang, and Chongjie Zhang · 2018
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Nervenet: Learning structured policy with graph neural networks
Tingwu Wang, Renjie Liao, Jimmy Ba, and Sanja Fidler · 2018
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Deep imitative models for flexible inference, planning, and control, 2018
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Hierarchical reinforcement learning with parameters
Maciej Klimek, Henryk Michalewski, Piotr Mi, et al · 2017
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Imitation from observation: Learning to imitate behaviors from raw video via context translation, 2017
YuXuan Liu, Abhishek Gupta, Pieter Abbeel, and Sergey Levine · 2017
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An algorithmic perspective on imitation learning
Takayuki Osa, Joni Pajarinen, Gerhard Neumann, J Andrew Bagnell, Pieter Abbeel, Jan Peters, et al · 2018
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Deep imitation learning for complex manipulation tasks from virtual reality teleoperation
T. Zhang, Z. McCarthy, O. Jow, D. Lee, X. Chen, K. Goldberg, and P. Abbeel · 2018
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Hierarchical approaches for reinforcement learning in parameterized action space
Ermo Wei, Drew Wicke, and Sean Luke · 2018
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Jiechao Xiong, Qing Wang, Zhuoran Yang, Peng Sun, Lei Han, Yang Zheng, Haobo Fu, Tong Zhang, Ji Liu, and Han Liu · 2018
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Nicholas Rhinehart, Rowan McAllister, and Sergey Levine · 2018
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Graph attention networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018
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Efficient bimanual manipulation using learned task schemas
Rohan Chitnis, Shubham Tulsiani, Saurabh Gupta, and Abhinav Gupta · 2019
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Hierarchical variational imitation learning of control programs
Roy Fox, Richard Shin, William Paul, Yitian Zou, Dawn Song, Ken Goldberg, Pieter Abbeel, and Ion Stoica · 2019
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Conditional neural movement primitives
M Yunus Seker, Mert Imre, Justus Piater, and Emre Ugur · 2019
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Compile: Compositional imitation learning and execution
Thomas Kipf, Yujia Li, Hanjun Dai, Vinicius Zambaldi, Alvaro Sanchez-Gonzalez, Edward Grefenstette, Pushmeet Kohli, and Peter Battaglia · 2019
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Dynamics learning with cascaded variational inference for multi-step manipulation
Kuan Fang, Yuke Zhu, Animesh Garg, Silvio Savarese, and Li Fei-Fei · 2019
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Contrastive learning of structured world models
Thomas Kipf, Elise van der Pol, and Max Welling · 2019
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Pybullet, a python module for physics simulation for games, robotics and machine learning
Erwin Coumans and Yunfei Bai · 2019
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