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Applying end-to-end learning to solve complex, interactive, pixel-driven control tasks on a robot is an unsolved problem.
Transfer learning for reinforcement learning on a physical robot
S. Barrett, M. E. Taylor, and P. Stone · 2010
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Mujoco: A physics engine for model-based control
E. Todorov, T. Erez, and Y. Tassa · 2012
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Learning neural network policies with guided policy search under unknown dynamics
S. Levine and P. Abbeel · 2014
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Deep domain confusion: Maximizing for domain invariance
E. Tzeng, J. Hoffman, N. Zhang, K. Saenko, and T. Darrell · 2014
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Domain-adversarial neural networks
H. Ajakan, P. Germain, H. Larochelle, F. Laviolette, and M. Marchand · 2014
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Trust region policy optimization
J. Schulman, S. Levine, P. Moritz, M. I. Jordan, and P. Abbeel · 2015
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Learning continuous control policies by stochastic value gradients
N. Heess, G. Wayne, D. Silver, T. P. Lillicrap, T. Erez, and Y. Tassa · 2015
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Learning deep object detectors from 3d models
X. Peng, B. Sun, K. Ali, and K. Saenko · 2015
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Render for CNN: viewpoint estimation in images using cnns trained with rendered 3d model views
H. Su, C. R. Qi, Y. Li, and L. J. Guibas · 2015
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Learning transferable features with deep adaptation networks
M. Long, Y. Cao, J. Wang, and M. I. Jordan · 2015
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Simultaneous deep transfer across domains and tasks
E. Tzeng, J. Hoffman, T. Darrell, and K. Saenko · 2015
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Towards adapting deep visuomotor representations from simulated to real environments
E. Tzeng, C. Devin, J. Hoffman, C. Finn, X. Peng, S. Levine, K. Saenko, and T. Darrell · 2015
Cited alongside, same era.
Learning contact-rich manipulation skills with guided policy search
S. Levine, N. Wagener, and P. Abbeel · 2015
Cited alongside, same era.
Human-level control through deep reinforcement learning
V. Mnih, K. Kavukcuoglu, D. Silver, A. Rusu, J. Veness, M. Bellemare, A. Graves, M. Riedmiller, A. Fidjeland, G. Ostrovski, S. Petersen, C. Beattie, A. Sadik, I. Antonoglou, H. King, D. Kumaran, D. Wierstra, S. Legg, and D. Hassabis · 2015
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A. Rusu, N. Rabinowitz, G. Desjardins, H. Soyer, J. Kirkpatrick, K. Kavukcuoglu, R. Pascanu, and R. Hadsell · 2016
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Domain-adversarial training of neural networks
Y. Ganin, E. Ustinova, H. Ajakan, P. Germain, H. Larochelle, F. Laviolette, M. Marchand, and V. Lempitsky · 2016
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Domain separation networks
K. Bousmalis, G. Trigeorgis, N. Silberman, D. Krishnan, and D. Erhan · 2016
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3D Simulation for Robot Arm Control with Deep Q-Learning
S. James and E. Johns · 2016
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End-to-end training of deep visuomotor policies
S. Levine, C. Finn, T. Darrell, and P. Abbeel · 2016
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Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours
L. Pinto and A. Gupta · 2016
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T. P. Lillicrap, J. J. Hunt, A. Pritzel, N. Heess, T. Erez, Y. Tassa, D. Silver, and D. Wierstra · 2016
Cited alongside, same era.
High-dimensional continuous control using generalized advantage estimation
J. Schulman, P. Moritz, S. Levine, M. Jordan, and P. Abbeel · 2016
Cited alongside, same era.
Asynchronous methods for deep reinforcement learning
V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu · 2016
Cited alongside, same era.
Continuous deep q-learning with model-based acceleration
S. Gu, T. P. Lillicrap, I. Sutskever, and S. Levine · 2016
Cited alongside, same era.
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Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection
S. Levine, P. Pastor, A. Krizhevsky, J. Ibarz, and D. Quillen · 2016
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Target-driven visual navigation in indoor scenes using deep reinforcement learning
Y. Zhu, R. Mottaghi, E. Kolve, J. J. Lim, A. Gupta, L. Fei-Fei, and A. Farhadi · 2017
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