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Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban

Oct 03, 2020
Peter Karkus, Mehdi Mirza, Arthur Guez, Andrew Jaegle, Timothy Lillicrap, Lars Buesing, Nicolas Heess, Theophane Weber


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Physically Embedded Planning Problems: New Challenges for Reinforcement Learning

Sep 11, 2020
Mehdi Mirza, Andrew Jaegle, Jonathan J. Hunt, Arthur Guez, Saran Tunyasuvunakool, Alistair Muldal, Théophane Weber, Peter Karkus, Sébastien Racanière, Lars Buesing, Timothy Lillicrap, Nicolas Heess


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Value-driven Hindsight Modelling

Feb 19, 2020
Arthur Guez, Fabio Viola, Théophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess

* 8 pages + reference + appendix 

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Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model

Nov 19, 2019
Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel, Timothy Lillicrap, David Silver


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Augmenting learning using symmetry in a biologically-inspired domain

Oct 01, 2019
Shruti Mishra, Abbas Abdolmaleki, Arthur Guez, Piotr Trochim, Doina Precup


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An investigation of model-free planning

Jan 11, 2019
Arthur Guez, Mehdi Mirza, Karol Gregor, Rishabh Kabra, Sébastien Racanière, Théophane Weber, David Raposo, Adam Santoro, Laurent Orseau, Tom Eccles, Greg Wayne, David Silver, Timothy Lillicrap


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Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search

Nov 15, 2018
Lars Buesing, Theophane Weber, Yori Zwols, Sebastien Racaniere, Arthur Guez, Jean-Baptiste Lespiau, Nicolas Heess


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Learning to Search with MCTSnets

Jul 17, 2018
Arthur Guez, Théophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Rémi Munos, David Silver

* ICML 2018 (camera-ready version) 

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Imagination-Augmented Agents for Deep Reinforcement Learning

Feb 14, 2018
Théophane Weber, Sébastien Racanière, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adria Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter Battaglia, Demis Hassabis, David Silver, Daan Wierstra


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Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

Dec 05, 2017
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy Lillicrap, Karen Simonyan, Demis Hassabis


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The Predictron: End-To-End Learning and Planning

Jul 20, 2017
David Silver, Hado van Hasselt, Matteo Hessel, Tom Schaul, Arthur Guez, Tim Harley, Gabriel Dulac-Arnold, David Reichert, Neil Rabinowitz, Andre Barreto, Thomas Degris

* Camera-ready version, ICML 2017, with supplement 

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Learning values across many orders of magnitude

Aug 16, 2016
Hado van Hasselt, Arthur Guez, Matteo Hessel, Volodymyr Mnih, David Silver

* Paper accepted for publication at NIPS 2016. This version includes the appendix 

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Increasing the Action Gap: New Operators for Reinforcement Learning

Dec 15, 2015
Marc G. Bellemare, Georg Ostrovski, Arthur Guez, Philip S. Thomas, Rémi Munos

* Bellemare, Marc G., Ostrovski, G., Guez, A., Thomas, Philip S., and Munos, Remi. Increasing the Action Gap: New Operators for Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 2016 

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Deep Reinforcement Learning with Double Q-learning

Dec 08, 2015
Hado van Hasselt, Arthur Guez, David Silver

* AAAI 2016 

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Better Optimism By Bayes: Adaptive Planning with Rich Models

Feb 09, 2014
Arthur Guez, David Silver, Peter Dayan

* 11 pages, 11 figures 

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Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search

Dec 18, 2013
Arthur Guez, David Silver, Peter Dayan

* (2012) Advances in Neural Information Processing Systems 25, pages 1034-1042 
* 14 pages, 7 figures, includes supplementary material. Advances in Neural Information Processing Systems (NIPS) 2012 

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