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2020 – today
- 2024
[i24]Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Ávila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana Borsa, Arthur Guez, Will Dabney:
A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning. CoRR abs/2406.02035 (2024)- 2023
- [i23]Veronica Chelu, Tom Zahavy, Arthur Guez, Doina Precup, Sebastian Flennerhag:
Optimism and Adaptivity in Policy Optimization. CoRR abs/2306.10587 (2023) - 2022
- [c21]Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez:
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation. ICLR 2022 - [c20]Ivo Danihelka, Arthur Guez, Julian Schrittwieser, David Silver:
Policy improvement by planning with Gumbel. ICLR 2022 - [c19]Anirudh Goyal, Abram L. Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adrià Puigdomènech Badia, Arthur Guez, Mehdi Mirza, Peter Conway Humphreys, Ksenia Konyushkova, Michal Valko, Simon Osindero, Timothy P. Lillicrap, Nicolas Heess, Charles Blundell:
Retrieval-Augmented Reinforcement Learning. ICML 2022: 7740-7765 - [c18]Peter Conway Humphreys, Arthur Guez, Olivier Tieleman, Laurent Sifre, Theophane Weber, Timothy P. Lillicrap:
Large-Scale Retrieval for Reinforcement Learning. NeurIPS 2022 - [i22]Anirudh Goyal, Abram L. Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adrià Puigdomènech Badia, Arthur Guez, Mehdi Mirza, Ksenia Konyushkova, Michal Valko, Simon Osindero, Timothy P. Lillicrap, Nicolas Heess, Charles Blundell:
Retrieval-Augmented Reinforcement Learning. CoRR abs/2202.08417 (2022) - [i21]Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez:
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation. CoRR abs/2204.08957 (2022) - [i20]Peter Conway Humphreys, Arthur Guez, Olivier Tieleman, Laurent Sifre, Théophane Weber, Timothy P. Lillicrap:
Large-Scale Retrieval for Reinforcement Learning. CoRR abs/2206.05314 (2022) - 2021
- [c17]Jessica B. Hamrick, Abram L. Friesen, Feryal M. P. Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Holger Buesing, Petar Velickovic, Theophane Weber:
On the role of planning in model-based deep reinforcement learning. ICLR 2021 - [c16]Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt:
Muesli: Combining Improvements in Policy Optimization. ICML 2021: 4214-4226 - [c15]Thomas Mesnard, Theophane Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas S. Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Rémi Munos:
Counterfactual Credit Assignment in Model-Free Reinforcement Learning. ICML 2021: 7654-7664 - [i19]Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt:
Muesli: Combining Improvements in Policy Optimization. CoRR abs/2104.06159 (2021) - 2020
- [j5]Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel, Timothy P. Lillicrap, David Silver
:
Mastering Atari, Go, chess and shogi by planning with a learned model. Nat. 588(7839): 604-609 (2020) - [c14]Arthur Guez, Fabio Viola, Theophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess:
Value-driven Hindsight Modelling. NeurIPS 2020 - [i18]Arthur Guez, Fabio Viola, Théophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess:
Value-driven Hindsight Modelling. CoRR abs/2002.08329 (2020) - [i17]Mehdi Mirza, Andrew Jaegle, Jonathan J. Hunt, Arthur Guez, Saran Tunyasuvunakool, Alistair Muldal, Théophane Weber, Péter Karkus, Sébastien Racanière, Lars Buesing, Timothy P. Lillicrap, Nicolas Heess:
Physically Embedded Planning Problems: New Challenges for Reinforcement Learning. CoRR abs/2009.05524 (2020) - [i16]Péter Karkus, Mehdi Mirza, Arthur Guez, Andrew Jaegle, Timothy P. Lillicrap, Lars Buesing, Nicolas Heess, Theophane Weber:
Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban. CoRR abs/2010.01298 (2020) - [i15]Jessica B. Hamrick, Abram L. Friesen, Feryal M. P. Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Buesing, Petar Velickovic, Théophane Weber:
On the role of planning in model-based deep reinforcement learning. CoRR abs/2011.04021 (2020) - [i14]Thomas Mesnard, Théophane Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Tom Stepleton, Nicolas Heess, Arthur Guez, Marcus Hutter, Lars Buesing, Rémi Munos:
Counterfactual Credit Assignment in Model-Free Reinforcement Learning. CoRR abs/2011.09464 (2020)
2010 – 2019
- 2019
- [c13]Lars Buesing, Theophane Weber, Yori Zwols, Nicolas Heess, Sébastien Racanière, Arthur Guez, Jean-Baptiste Lespiau:
Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search. ICLR (Poster) 2019 - [c12]Arthur Guez, Mehdi Mirza, Karol Gregor, Rishabh Kabra, Sébastien Racanière, Theophane Weber, David Raposo, Adam Santoro, Laurent Orseau, Tom Eccles, Greg Wayne, David Silver, Timothy P. Lillicrap:
An Investigation of Model-Free Planning. ICML 2019: 2464-2473 - [i13]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 P. Lillicrap:
An investigation of model-free planning. CoRR abs/1901.03559 (2019) - [i12]Shruti Mishra, Abbas Abdolmaleki, Arthur Guez, Piotr Trochim, Doina Precup:
Augmenting learning using symmetry in a biologically-inspired domain. CoRR abs/1910.00528 (2019) - [i11]Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel, Timothy P. Lillicrap, David Silver:
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model. CoRR abs/1911.08265 (2019) - 2018
- [c11]Moritz Krusche, Eric Schulz, Arthur Guez, Maarten Speekenbrink:
Adaptive planning in human search. CogSci 2018 - [c10]Arthur Guez, Theophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Rémi Munos, David Silver:
Learning to Search with MCTSnets. ICML 2018: 1817-1826 - [i10]Arthur Guez, Théophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Rémi Munos, David Silver:
Learning to Search with MCTSnets. CoRR abs/1802.04697 (2018) - [i9]Lars Buesing, Theophane Weber, Yori Zwols, Sébastien Racanière, Arthur Guez, Jean-Baptiste Lespiau, Nicolas Heess:
Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search. CoRR abs/1811.06272 (2018) - 2017
- [j4]David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy P. Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel, Demis Hassabis:
Mastering the game of Go without human knowledge. Nat. 550(7676): 354-359 (2017) - [c9]David Silver, Hado van Hasselt, Matteo Hessel, Tom Schaul, Arthur Guez, Tim Harley, Gabriel Dulac-Arnold, David P. Reichert, Neil C. Rabinowitz, André Barreto, Thomas Degris:
The Predictron: End-To-End Learning and Planning. ICML 2017: 3191-3199 - [c8]Sébastien Racanière, Theophane Weber, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter W. Battaglia, Demis Hassabis, David Silver, Daan Wierstra:
Imagination-Augmented Agents for Deep Reinforcement Learning. NIPS 2017: 5690-5701 - [i8]Theophane Weber, Sébastien Racanière, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter W. Battaglia, David Silver, Daan Wierstra:
Imagination-Augmented Agents for Deep Reinforcement Learning. CoRR abs/1707.06203 (2017) - [i7]David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy P. Lillicrap, Karen Simonyan, Demis Hassabis:
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm. CoRR abs/1712.01815 (2017) - 2016
- [j3]David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Vedavyas Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy P. Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, Demis Hassabis:
Mastering the game of Go with deep neural networks and tree search. Nat. 529(7587): 484-489 (2016) - [c7]Marc G. Bellemare, Georg Ostrovski, Arthur Guez, Philip S. Thomas, Rémi Munos:
Increasing the Action Gap: New Operators for Reinforcement Learning. AAAI 2016: 1476-1483 - [c6]Hado van Hasselt, Arthur Guez, David Silver:
Deep Reinforcement Learning with Double Q-Learning. AAAI 2016: 2094-2100 - [c5]Hado van Hasselt, Arthur Guez, Matteo Hessel, Volodymyr Mnih, David Silver:
Learning values across many orders of magnitude. NIPS 2016: 4287-4295 - [i6]Hado van Hasselt, Arthur Guez, Matteo Hessel, David Silver:
Learning functions across many orders of magnitudes. CoRR abs/1602.07714 (2016) - [i5]David Silver, Hado van Hasselt, Matteo Hessel, Tom Schaul, Arthur Guez, Tim Harley, Gabriel Dulac-Arnold, David P. Reichert, Neil C. Rabinowitz, André Barreto, Thomas Degris:
The Predictron: End-To-End Learning and Planning. CoRR abs/1612.08810 (2016) - 2015
- [i4]Hado van Hasselt, Arthur Guez, David Silver:
Deep Reinforcement Learning with Double Q-learning. CoRR abs/1509.06461 (2015) - [i3]Marc G. Bellemare, Georg Ostrovski, Arthur Guez, Philip S. Thomas, Rémi Munos:
Increasing the Action Gap: New Operators for Reinforcement Learning. CoRR abs/1512.04860 (2015) - 2014
- [c4]Arthur Guez, Nicolas Heess, David Silver, Peter Dayan:
Bayes-Adaptive Simulation-based Search with Value Function Approximation. NIPS 2014: 451-459 - [i2]Arthur Guez, David Silver, Peter Dayan:
Better Optimism By Bayes: Adaptive Planning with Rich Models. CoRR abs/1402.1958 (2014) - 2013
- [j2]Arthur Guez, David Silver, Peter Dayan:
Scalable and Efficient Bayes-Adaptive Reinforcement Learning Based on Monte-Carlo Tree Search. J. Artif. Intell. Res. 48: 841-883 (2013) - 2012
- [c3]Arthur Guez, David Silver, Peter Dayan:
Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search. NIPS 2012: 1034-1042 - [i1]Arthur Guez, David Silver, Peter Dayan:
Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search. CoRR abs/1205.3109 (2012) - 2010
- [c2]Arthur Guez, Joelle Pineau:
Multi-tasking SLAM. ICRA 2010: 377-384
2000 – 2009
- 2009
- [j1]Joelle Pineau, Arthur Guez, Robert D. Vincent, Gabriella Panuccio, Massimo Avoli:
Treating Epilepsy via Adaptive Neurostimulation: a Reinforcement Learning Approach. Int. J. Neural Syst. 19(4): 227-240 (2009) - 2008
- [c1]Arthur Guez, Robert D. Vincent, Massimo Avoli, Joelle Pineau:
Adaptive Treatment of Epilepsy via Batch-mode Reinforcement Learning. AAAI 2008: 1671-1678
Coauthor Index
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