publication . Preprint . 2016

Learning to Act by Predicting the Future

Dosovitskiy, Alexey; Koltun, Vladlen;
Open Access English
  • Published: 06 Nov 2016
Abstract
Comment: Published as a conference paper at ICLR 2017
Subjects
free text keywords: Computer Science - Learning, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
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50 references, page 1 of 4

Karen E. Adolph and Sarah E. Berger. Motor development. In Handbook of Child Psychology, volume 2, pp. 161-213. Wiley, 6th edition, 2006.

Andrew G. Barto and Sridhar Mahadevan. Recent advances in hierarchical reinforcement learning. Discrete Event Dynamic Systems, 13(1-2), 2003.

Dimitri P. Bertsekas. A counterexample to temporal differences learning. Neural Computation, 7(2), 1995.

Dimitri P. Bertsekas. Pathologies of temporal difference methods in approximate dynamic programming. In IEEE Conference on Decision and Control, 2010. [OpenAIRE]

Charles Blundell, Benigno Uria, Alexander Pritzel, Yazhe Li, Avraham Ruderman, Joel Z. Leibo, Jack Rae, Daan Wierstra, and Demis Hassabis. Model-free episodic control. arXiv:1606.04460, 2016. [OpenAIRE]

Bruno Castro da Silva, George Konidaris, and Andrew G. Barto. Learning parameterized skills. In ICML, 2012.

Marc Peter Deisenroth, Peter Englert, Jan Peters, and Dieter Fox. Multi-task policy search for robotics. In ICRA, 2014. [OpenAIRE]

Eyal Even-Dar and Yishay Mansour. Learning rates for Q-learning. JMLR, 5, 2003.

Chelsea Finn, Ian J. Goodfellow, and Sergey Levine. Unsupervised learning for physical interaction through video prediction. In NIPS, 2016.

Zolta´n Ga´bor, Zsolt Kalma´r, and Csaba Szepesva´ri. Multi-criteria reinforcement learning. In ICML, 1998.

Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Delving deep into rectifiers: Surpassing humanlevel performance on ImageNet classification. In ICCV, 2015.

Michael I. Jordan and David E. Rumelhart. Forward models: Supervised learning with a distal teacher. Cognitive Science, 16(3), 1992.

Leslie Pack Kaelbling, Michael L. Littman, and Andrew W. Moore. Reinforcement learning: A survey. JAIR, 4, 1996. [OpenAIRE]

Nal Kalchbrenner, Aaron van den Oord, Karen Simonyan, Ivo Danihelka, Oriol Vinyals, Alex Graves, and Koray Kavukcuoglu. Video pixel networks. arXiv:1610.00527, 2016. [OpenAIRE]

Michał Kempka, Marek Wydmuch, Grzegorz Runc, Jakub Toczek, and Wojciech Jas´kowski. ViZDoom: A Doom-based AI research platform for visual reinforcement learning. In IEEE Conference on Computational Intelligence and Games, 2016. [OpenAIRE]

50 references, page 1 of 4
Abstract
Comment: Published as a conference paper at ICLR 2017
Subjects
free text keywords: Computer Science - Learning, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Download from
50 references, page 1 of 4

Karen E. Adolph and Sarah E. Berger. Motor development. In Handbook of Child Psychology, volume 2, pp. 161-213. Wiley, 6th edition, 2006.

Andrew G. Barto and Sridhar Mahadevan. Recent advances in hierarchical reinforcement learning. Discrete Event Dynamic Systems, 13(1-2), 2003.

Dimitri P. Bertsekas. A counterexample to temporal differences learning. Neural Computation, 7(2), 1995.

Dimitri P. Bertsekas. Pathologies of temporal difference methods in approximate dynamic programming. In IEEE Conference on Decision and Control, 2010. [OpenAIRE]

Charles Blundell, Benigno Uria, Alexander Pritzel, Yazhe Li, Avraham Ruderman, Joel Z. Leibo, Jack Rae, Daan Wierstra, and Demis Hassabis. Model-free episodic control. arXiv:1606.04460, 2016. [OpenAIRE]

Bruno Castro da Silva, George Konidaris, and Andrew G. Barto. Learning parameterized skills. In ICML, 2012.

Marc Peter Deisenroth, Peter Englert, Jan Peters, and Dieter Fox. Multi-task policy search for robotics. In ICRA, 2014. [OpenAIRE]

Eyal Even-Dar and Yishay Mansour. Learning rates for Q-learning. JMLR, 5, 2003.

Chelsea Finn, Ian J. Goodfellow, and Sergey Levine. Unsupervised learning for physical interaction through video prediction. In NIPS, 2016.

Zolta´n Ga´bor, Zsolt Kalma´r, and Csaba Szepesva´ri. Multi-criteria reinforcement learning. In ICML, 1998.

Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Delving deep into rectifiers: Surpassing humanlevel performance on ImageNet classification. In ICCV, 2015.

Michael I. Jordan and David E. Rumelhart. Forward models: Supervised learning with a distal teacher. Cognitive Science, 16(3), 1992.

Leslie Pack Kaelbling, Michael L. Littman, and Andrew W. Moore. Reinforcement learning: A survey. JAIR, 4, 1996. [OpenAIRE]

Nal Kalchbrenner, Aaron van den Oord, Karen Simonyan, Ivo Danihelka, Oriol Vinyals, Alex Graves, and Koray Kavukcuoglu. Video pixel networks. arXiv:1610.00527, 2016. [OpenAIRE]

Michał Kempka, Marek Wydmuch, Grzegorz Runc, Jakub Toczek, and Wojciech Jas´kowski. ViZDoom: A Doom-based AI research platform for visual reinforcement learning. In IEEE Conference on Computational Intelligence and Games, 2016. [OpenAIRE]

50 references, page 1 of 4
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