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Skilled robot task learning is best implemented by predictive action policies due to the inherent latency of sensorimotor processes.
A. J. Ijspeert, J. Nakanishi, and S. Schaal, “Learning attractor landscapes for learning motor primitives,” NIPS , 2003
2003
Earlier work this paper cites.
J. Kocijan, R. Murray-Smith, C. E. Rasmussen, and A. Girard, “Gaussian process model based predictive control,” in ACC , 2004
2004
Earlier work this paper cites.
S. B. Most, B. J. Scholl, E. R. Clifford, and D. J. Simons, “What you see is what you set: sustained inattentional blindness and the capture of awareness.” Psychological review , vol. 112, no. 1, p. 217, 2005
2005
Earlier work this paper cites.
S. Jodogne and J. H. Piater, “Closed-loop learning of visual control policies,” Journal of Artificial Intelligence Research , vol. 28, pp. 349–391, 2007
2007
Earlier work this paper cites.
J. Kober and J. R. Peters, “Policy search for motor primitives in robotics,” in NIPS , 2009
2009
Earlier work this paper cites.
J. T. Betts, Practical methods for optimal control and estimation using nonlinear programming . SIAM, 2010
2010
Earlier work this paper cites.
J. Kober, E. Oztop, and J. Peters, “Reinforcement learning to adjust robot movements to new situations,” in RSS , 2010
2010
Earlier work this paper cites.
D. M. Wolpert, J. Diedrichsen, and J. R. Flanagan, “Principles of sensorimotor learning,” Nature Reviews Neuroscience , vol. 12, no. 12, pp. 739–751, 2011
2011
Earlier work this paper cites.
S. Lange, M. Riedmiller, and A. Voigtlander, “Autonomous reinforcement learning on raw visual input data in a real world application,” in IJCNN , 2012
2012
Earlier work this paper cites.
J. Kober, J. A. Bagnell, and J. Peters, “Reinforcement learning in robotics: A survey,” The International Journal of Robotics Research , vol. 32, no. 11, pp. 1238–1274, 2013
2013
Earlier work this paper cites.
M. P. Deisenroth, G. Neumann, J. Peters et al. , “A survey on policy search for robotics,” Foundations and Trends in Robotics , vol. 2, no. 1–2, pp. 1–142, 2013
2013
Cited alongside, same era.
E. F. Camacho and C. B. Alba, Model predictive control . Springer Science & Business Media, 2013
2013
Cited alongside, same era.
R. Jonschkowski and O. Brock, “State representation learning in robotics: Using prior knowledge about physical interaction,” in RSS , 2014
2014
Cited alongside, same era.
S. Levine and P. Abbeel, “Learning neural network policies with guided policy search under unknown dynamics,” in NIPS , 2014
2014
Cited alongside, same era.
D. P. Kingma and M. Welling, “Auto-encoding variational Bayes,” in ICLR , 2014
2014
Cited alongside, same era.
2015
Later among the works it cites.
J. Schulman, S. Levine, P. Abbeel, M. I. Jordan, and P. Moritz, “Trust region policy optimization.” in ICML , 2015, pp. 1889–1897
2015
Later among the works it cites.
A. Ghadirzadeh, J. Bütepage, A. Maki, D. Kragic, and M. Björkman, “A sensorimotor reinforcement learning framework for physical human-robot interaction,” in IROS , 2016
2016
Later among the works it cites.
C. Finn, X. Y. Tan, Y. Duan, T. Darrell, S. Levine, and P. Abbeel, “Deep spatial autoencoders for visuomotor learning,” in ICRA , 2016
2016
Later among the works it cites.
H. van Hoof, N. Chen, M. Karl, P. van der Smagt, and J. Peters, “Stable reinforcement learning with autoencoders for tactile and visual data,” in IROS , 2016
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2014
Cited alongside, same era.
M. Watter, J. Springenberg, J. Boedecker, and M. Riedmiller, “Embed to control: A locally linear latent dynamics model for control from raw images,” in NIPS , 2015
2015
Cited alongside, same era.
N. Wahlström, T. B. Schön, and M. P. Deisenroth, “Learning deep dynamical models from image pixels,” IFAC-PapersOnLine , vol. 48, no. 28, pp. 1059–1064, 2015
2015
Cited alongside, same era.
A. Ghadirzadeh, A. Maki, and M. Björkman, “A sensorimotor approach for self-learning of hand-eye coordination,” in IROS , 2015
2015
Cited alongside, same era.
V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness, M. G. Bellemare, A. Graves, M. Riedmiller, A. K. Fidjeland, G. Ostrovski et al. , “Human-level control through deep reinforcement learning,” Nature , vol. 518, no. 7540, pp. 529–533, 2015
2015
Cited alongside, same era.
Cited in the paper.
Cited in the paper.
2016
Later among the works it cites.
S. Levine, C. Finn, T. Darrell, and P. Abbeel, “End-to-end training of deep visuomotor policies,” Journal of Machine Learning Research , vol. 17, no. 39, pp. 1–40, 2016
2016
Later among the works it cites.
A. Ghadirzadeh, J. Bütepage, D. Kragic, and M. Björkman, “Self-learning and adaptation in a sensorimotor framework,” in ICRA , 2016
2016
Later among the works it cites.
P. Agrawal, A. Nair, P. Abbeel, J. Malik, and S. Levine, “Learning to poke by poking: Experiential learning of intuitive physics,” in NIPS , 2016
2016
Later among the works it cites.
C. Doersch, “Tutorial on variational autoencoders,” arXiv preprint arXiv:1606.05908 , 2016
2016
Later among the works it cites.
Y. Duan, X. Chen, R. Houthooft, J. Schulman, and P. Abbeel, “Benchmarking deep reinforcement learning for continuous control,” in ICML , 2016
2016
Later among the works it cites.