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We propose a model-free deep reinforcement learning method that leverages a small amount of demonstration data to assist a reinforcement learning agent.
Policy invariance under reward transformations: Theory and application to reward shaping
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Sham Kakade and John Langford · 2002
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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 J Gordon, and Drew Bagnell · 2011
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Reinforcement learning in robotics: A survey
Jens Kober and Jan Peters · 2012
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Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
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A survey on policy search for robotics
Marc Peter Deisenroth, Gerhard Neumann, Jan Peters, et al · 2013
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Guided policy search
Sergey Levine and Vladlen Koltun · 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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Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 2014
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Deterministic policy gradient algorithms
David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, and Martin Riedmiller · 2014
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Learning continuous control policies by stochastic value gradients
Nicolas Heess, Gregory Wayne, David Silver, Tim Lillicrap, Tom Erez, and Yuval Tassa · 2015
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End-to-end training of deep visuomotor policies
Sergey Levine, Chelsea Finn, Trevor Darrell, and Pieter Abbeel · 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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Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours
Lerrel Pinto and Abhinav Gupta · 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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Guided cost learning: Deep inverse optimal control via policy optimization
Chelsea Finn, Sergey Levine, and Pieter Abbeel · 2016
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Learning dexterous manipulation for a soft robotic hand from human demonstration
Abhishek Gupta, Clemens Eppner, Sergey Levine, and Pieter Abbeel · 2016
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Learning and transfer of modulated locomotor controllers
Nicolas Heess, Greg Wayne, Yuval Tassa, Timothy Lillicrap, Martin Riedmiller, and David Silver · 2016
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Generative adversarial imitation learning
Jonathan Ho and Stefano Ermon · 2016
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Reinforcement learning with unsupervised auxiliary tasks
Max Jaderberg, Volodymyr Mnih, Wojciech Marian Czarnecki, Tom Schaul, Joel Z Leibo, David Silver, and Koray Kavukcuoglu · 2016
Inferring the latent structure of human decision-making from raw visual inputs
Yunzhu Li, Jiaming Song, and Stefano Ermon · 2017
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Imitation from observation: Learning to imitate behaviors from raw video via context translation
Yuxuan Liu, Abhishek Gupta, Pieter Abbeel, and Sergey Levine · 2017
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Learning human behaviors from motion capture by adversarial imitation
Josh Merel, Yuval Tassa, Dhruva TB, Sriram Srinivasan, Jay Lemmon, Ziyu Wang, Greg Wayne, and Nicolas Heess · 2017
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Overcoming exploration in reinforcement learning with demonstrations
Ashvin Nair, Bob McGrew, Marcin Andrychowicz, Wojciech Zaremba, and Pieter Abbeel · 2017
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Learning dexterous manipulation policies from experience and imitation
Vikash Kumar, Abhishek Gupta, Emanuel Todorov, and Sergey Levine · 2016
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Sergey Levine, Peter Pastor, Alex Krizhevsky, and Deirdre Quillen · 2016
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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
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Mastering the game of go with deep neural networks and tree search
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, et al · 2016
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Collective robot reinforcement learning with distributed asynchronous guided policy search
Ali Yahya, Adrian Li, Mrinal Kalakrishnan, Yevgen Chebotar, and Sergey Levine · 2016
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Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping
Konstantinos Bousmalis, Alex Irpan, Paul Wohlhart, Yunfei Bai, Matthew Kelcey, Mrinal Kalakrishnan, Laura Downs, Julian Ibarz, Peter Pastor, Kurt Konolige, Sergey Levine, and Vincent Vanhoucke · 2017
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Path integral guided policy search
Yevgen Chebotar, Mrinal Kalakrishnan, Ali Yahya, Adrian Li, Stefan Schaal, and Sergey Levine · 2017
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Xue Bin Peng, Marcin Andrychowicz, Wojciech Zaremba, and Pieter Abbeel · 2017
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Asymmetric Actor Critic for Image-Based Robot Learning
Lerrel Pinto, Marcin Andrychowicz, Peter Welinder, Wojciech Zaremba, and Pieter Abbeel · 2017
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Data-efficient deep reinforcement learning for dexterous manipulation
Ivaylo Popov, Nicolas Heess, Timothy P. Lillicrap, Roland Hafner, Gabriel Barth-Maron, Matej Vecerik, Thomas Lampe, Yuval Tassa, Tom Erez, and Martin A. Riedmiller · 2017
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Rouhollah Rahmatizadeh, Pooya Abolghasemi, Ladislau Bölöni, and Sergey Levine · 2017
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Learning complex dexterous manipulation with deep reinforcement learning and demonstrations
Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, John Schulman, Emanuel Todorov, and Sergey Levine · 2017
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Reasoning about liquids via closed-loop simulation
Connor Schenck and Dieter Fox · 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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Time-contrastive networks: Self-supervised learning from multi-view observation
Pierre Sermanet, Corey Lynch, Jasmine Hsu, and Sergey Levine · 2017
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Domain randomization for transferring deep neural networks from simulation to the real world
Joshua Tobin, Rachel Fong, Alex Ray, Jonas Schneider, Wojciech Zaremba, and Pieter Abbeel · 2017
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Leveraging demonstrations for deep reinforcement learning on robotics problems with sparse rewards
Matej Vecerik, Todd Hester, Jonathan Scholz, Fumin Wang, Olivier Pietquin, Bilal Piot, Nicolas Heess, Thomas Rothörl, Thomas Lampe, and Martin A. Riedmiller · 2017
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Learning a visuomotor controller for real world robotic grasping using easily simulated depth images
Ulrich Viereck, Andreas ten Pas, Kate Saenko, and Robert Platt · 2017
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Robust imitation of diverse behaviors
Ziyu Wang, Josh Merel, Scott E. Reed, Greg Wayne, Nando de Freitas, and Nicolas Heess · 2017
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