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Imitation learning has traditionally been applied to learn a single task from demonstrations thereof.
Efficient training of artificial neural networks for autonomous navigation
Dean A Pomerleau · 1991
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Reinforcement learning: An introduction, 1998
Richard S Sutton and Andrew G Barto · 1998
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Is imitation learning the route to humanoid robots?
Stefan Schaal · 1999
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Algorithms for inverse reinforcement learning
Andrew Y Ng, Stuart J Russell, et al · 2000
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Apprenticeship learning via inverse reinforcement learning
Pieter Abbeel and Andrew Y. Ng · 2004
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Robot programming by demonstration
Aude Billard, Sylvain Calinon, Ruediger Dillmann, and Stefan Schaal · 2008
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Maximum entropy inverse reinforcement learning
Brian D. Ziebart, Andrew L. Maas, J. Andrew Bagnell, and Anind K. Dey · 2008
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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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Efficient reductions for imitation learning
Stéphane Ross and Drew Bagnell · 2010
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Apprenticeship learning about multiple intentions
Monica Babes, Vukosi Marivate, Kaushik Subramanian, and Michael L Littman · 2011
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Bayesian multitask inverse reinforcement learning
Christos Dimitrakakis and Constantin A Rothkopf · 2011
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Learning force control policies for compliant manipulation
Mrinal Kalakrishnan, Ludovic Righetti, Peter Pastor, and Stefan Schaal · 2011
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Nonlinear inverse reinforcement learning with gaussian processes
Sergey Levine, Zoran Popovic, and Vladlen Koltun · 2011
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Learning to select and generalize striking movements in robot table tennis
Katharina Mülling, Jens Kober, Oliver Kroemer, and Jan Peters · 2013
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Incremental semantically grounded learning from demonstration
Scott Niekum, Sachin Chitta, Andrew G Barto, Bhaskara Marthi, and Sarah Osentoski · 2013
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Generative adversarial nets
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, and Yoshua Bengio · 2014
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Deep generative image models using a laplacian pyramid of adversarial networks
Emily L Denton, Soumith Chintala, Rob Fergus, et al · 2015
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Towards learning hierarchical skills for multi-phase manipulation tasks
Generative adversarial imitation learning
Jonathan Ho and Stefano Ermon · 2016
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Connecting generative adversarial networks and actor-critic methods
David Pfau and Oriol Vinyals · 2016
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Amortised map inference for image super-resolution
Casper Kaae Sønderby, Jose Caballero, Lucas Theis, Wenzhe Shi, and Ferenc Huszár · 2016
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Martín Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Oliver Kroemer, Christian Daniel, Gerhard Neumann, Herke Van Hoof, and Jan Peters · 2015
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Trust region policy optimization
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Path integral guided policy search
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Infogan: Interpretable representation learning by information maximizing generative adversarial nets, 2016
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Chelsea Finn, Paul Christiano, Pieter Abbeel, and Sergey Levine · 2016
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Yan Duan, Marcin Andrychowicz, Bradly Stadie, Jonathan Ho, Jonas Schneider, Ilya Sutskever, Pieter Abbeel, and Wojciech Zaremba · 2017
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Feudal networks for hierarchical reinforcement learning
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