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We consider a problem of learning the reward and policy from expert examples under unknown dynamics.
Efficient training of artificial neural networks for autonomous navigation
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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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Relative entropy inverse reinforcement learning
Abdeslam Boularias, Jens Kober, and Jan Peters · 2011
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A reduction of imitation learning and structured prediction to no-regret online learning
Stéphane Ross, Geoffrey Gordon, and Drew Bagnell · 2011
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Learning objective functions for manipulation
Mrinal Kalakrishnan, Peter Pastor, Ludovic Righetti, and Stefan Schaal · 2013
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Empowerment–an introduction
Christoph Salge, Cornelius Glackin, and Daniel Polani · 2014
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Variational information maximisation for intrinsically motivated reinforcement learning
Shakir Mohamed and Danilo Jimenez Rezende · 2015
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Trust region policy optimization
John Schulman, Sergey Levine, Pieter Abbeel, Michael Jordan, and Philipp Moritz · 2015
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Generative adversarial imitation learning
Jonathan Ho and Stefano Ermon · 2016
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Learning robust rewards with adversarial inverse reinforcement learning
Justin Fu, Katie Luo, and Sergey Levine · 2017
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Show, attend and interact: Perceivable human-robot social interaction through neural attention q-network
Ahmed. H Qureshi, Yutaka Nakamura, Yuichiro Yoshikawa, and Hiroshi Ishiguro · 2017
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Learning driving styles for autonomous vehicles from demonstration
Markus Kuderer, Shilpa Gulati, and Wolfram Burgard · 2015
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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, et al · 2015
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Chelsea Finn, Paul Christiano, Pieter Abbeel, and Sergey Levine
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Guided cost learning: Deep inverse optimal control via policy optimization
Chelsea Finn, Sergey Levine, and Pieter Abbeel
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John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Intrinsically motivated reinforcement learning for human–robot interaction in the real-world
Ahmed. H Qureshi, Yutaka Nakamura, Yuichiro Yoshikawa, and Hiroshi Ishiguro · 2018
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