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For an autonomous agent to fulfill a wide range of user-specified goals at test time, it must be able to learn broadly applicable and general-purpose skill repertoires.
Learning factorial codes by predictability minimization
Jürgen Schmidhuber · 1992
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Learning to achieve goals
L P Kaelbling · 1993
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The development of embodied cognition: Six lessons from babies
Linda Smith and Michael Gasser · 2005
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Deep learning of visual control policies
Sascha Lange and Martin A Riedmiller · 2010
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Horde: A Scalable Real-time Architecture for Learning Knowledge from Unsupervised Sensorimotor Interaction
Richard S Sutton, Joseph Modayil, Michael Delp, Thomas Degris, Patrick M Pilarski, Adam White, and Doina Precup · 2011
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Active Learning of Inverse Models with Intrinsically Motivated Goal Exploration in Robots
A Baranes and P-Y Oudeyer · 2012
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Disentangling factors of variation via generative entangling
Guillaume Desjardins, Aaron Courville, and Yoshua Bengio · 2012
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Autonomous reinforcement learning on raw visual input data in a real world application
Sascha Lange, Martin Riedmiller, Arne Voigtlander, and Arne Voigtländer · 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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Discovering hidden factors of variation in deep networks
Brian Cheung, Jesse A Livezey, Arjun K Bansal, and Bruno A Olshausen · 2014
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Auto-Encoding Variational Bayes
Diederik P Kingma and Max Welling · 2014
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Learning to disentangle factors of variation with manifold interaction
Scott Reed, Kihyuk Sohn, Yuting Zhang, and Honglak Lee · 2014
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Action-Conditional Video Prediction using Deep Networks in Atari Games
Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard Lewis, and Satinder Singh · 2015
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Image database TID2013: Peculiarities, results and perspectives
Nikolay Ponomarenko, Lina Jin, Oleg Ieremeiev, Vladimir Lukin, Karen Egiazarian, Jaakko Astola, Benoit Vozel, Kacem Chehdi, Marco Carli, Federica Battisti, and Others · 2015
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Universal Value Function Approximators
Tom Schaul, Daniel Horgan, Karol Gregor, and David Silver · 2015
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Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images
Manuel Watter, Jost Tobias Springenberg, Joschka Boedecker, and Martin Riedmiller · 2015
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Learning to Poke by Poking: Experiential Learning of Intuitive Physics
Pulkit Agrawal, Ashvin Nair, Pieter Abbeel, Jitendra Malik, and Sergey Levine · 2016
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Unifying count-based exploration and intrinsic motivation
Marc Bellemare, Sriram Srinivasan, Georg Ostrovski, Tom Schaul, David Saxton, and Remi Munos · 2016
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Infogan: Interpretable representation learning by information maximizing generative adversarial nets
Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel · 2016
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Deep Visual Foresight for Planning Robot Motion
Chelsea Finn and Sergey Levine · 2016
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Deep spatial autoencoders for visuomotor learning
Chelsea Finn, Xin Yu Tan, Yan Duan, Trevor Darrell, Sergey Levine, and Pieter Abbeel · 2016
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End-to-End Training of Deep Visuomotor Policies
Curiosity-Driven Exploration by Self-Supervised Prediction
Deepak Pathak, Pulkit Agrawal, Alexei A. Efros, and Trevor Darrell · 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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Hindsight policy gradients
Paulo Rauber, Filipe Mutz, and Juergen Jürgen Schmidhuber · 2017
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Sim-to-real robot learning from pixels with progressive nets
Andrei A Rusu, Matej Vecerik, Thomas Rothörl, Nicolas Heess, Razvan Pascanu, and Raia Hadsell · 2017
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Time-contrastive networks: Self-supervised learning from video
Pierre Sermanet, Corey Lynch, Yevgen Chebotar, Jasmine Hsu, Eric Jang, Stefan Schaal, and Sergey Levine · 2017
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Sergey Levine, Chelsea Finn, Trevor Darrell, and Pieter Abbeel · 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
Cited alongside, same era.
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Tim Harley, Timothy P Lillicrap, David Silver, Koray Kavukcuoglu, Korayk@google Com, and Google Deepmind · 2016
Cited alongside, same era.
Supersizing Self-supervision: Learning to Grasp from 50K Tries and 700 Robot Hours
Lerrel Pinto and Abhinav Gupta · 2016
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Hindsight Experience Replay
Marcin Andrychowicz, Filip Wolski, Alex Ray, Jonas Schneider, Rachel Fong, Peter Welinder, Bob Mcgrew, Josh Tobin, Pieter Abbeel, and Wojciech Zaremba · 2017
Cited alongside, same era.
Self-Supervised Visual Planning with Temporal Skip Connections
Frederik Ebert, Chelsea Finn, Alex X Lee, and Sergey Levine · 2017
Cited alongside, same era.
Stochastic neural networks for hierarchical reinforcement learning
Carlos Florensa, Yan Duan, and Pieter Abbeel · 2017
Cited alongside, same era.
Independently Controllable Factors
Valentin Thomas, Jules Pondard, Emmanuel Bengio, Marc Sarfati, Philippe Beaudoin, Marie-Jean Meurs, Joelle Pineau, Doina Precup, and Yoshua Bengio · 2017
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Diversity is All You Need: Learning Skills without a Reward Function
Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, and Sergey Levine · 2018
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Addressing Function Approximation Error in Actor-Critic Methods
Scott Fujimoto, Herke van Hoof, and David Meger · 2018
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David Ha and Jürgen Schmidhuber · 2018
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Zero-Shot Visual Imitation
Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo, Pulkit Agrawal, Dian Chen, Yide Shentu, Evan Shelhamer, Jitendra Malik, Alexei A Efros, and Trevor Darrell · 2018
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Unsupervised Learning of Goal Spaces for Intrinsically Motivated Goal Exploration
Alexandre Péré, Sebastien Forestier, Olivier Sigaud, and Pierre-Yves Oudeyer · 2018
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Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research
Matthias Plappert, Marcin Andrychowicz, Alex Ray, Bob Mcgrew, Bowen Baker, Glenn Powell, Jonas Schneider, Josh Tobin, Maciek Chociej, Peter Welinder, Vikash Kumar, and Wojciech Zaremba · 2018
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Temporal Difference Models: Model-Free Deep RL For Model-Based Control
Vitchyr Pong, Shixiang Gu, Murtaza Dalal, and Sergey Levine · 2018
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Aravind Srinivas, Allan Jabri, Pieter Abbeel, Sergey Levine, and Chelsea Finn · 2018
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The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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