Arthur Guez

According to our database, Arthur Guez authored at least 37 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning.

Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Ávila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana Borsa, Arthur Guez, Will Dabney

CoRR, 2024

2023

Optimism and Adaptivity in Policy Optimization.

Veronica Chelu, Tom Zahavy, Arthur Guez, Doina Precup, Sebastian Flennerhag

CoRR, 2023

2022

Retrieval-Augmented Reinforcement Learning.

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

CoRR, 2022

Large-Scale Retrieval for Reinforcement Learning.

Peter Conway Humphreys, Arthur Guez, Olivier Tieleman, Laurent Sifre, Theophane Weber, Timothy P. Lillicrap

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Retrieval-Augmented Reinforcement Learning.

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

Proceedings of the International Conference on Machine Learning, 2022

Policy improvement by planning with Gumbel.

Ivo Danihelka, Arthur Guez, Julian Schrittwieser, David Silver

Proceedings of the Tenth International Conference on Learning Representations, 2022

COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation.

Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Counterfactual Credit Assignment in Model-Free Reinforcement Learning.

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

Proceedings of the 38th International Conference on Machine Learning, 2021

Muesli: Combining Improvements in Policy Optimization.

Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt

Proceedings of the 38th International Conference on Machine Learning, 2021

On the role of planning in model-based deep reinforcement learning.

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

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Mastering Atari, Go, chess and shogi by planning with a learned model.

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

Nat., 2020

Counterfactual Credit Assignment in Model-Free Reinforcement Learning.

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

CoRR, 2020

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

Péter Karkus, Mehdi Mirza, Arthur Guez, Andrew Jaegle, Timothy P. Lillicrap, Lars Buesing, Nicolas Heess, Theophane Weber

CoRR, 2020

Physically Embedded Planning Problems: New Challenges for Reinforcement Learning.

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

CoRR, 2020

Value-driven Hindsight Modelling.

Arthur Guez, Fabio Viola, Theophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Augmenting learning using symmetry in a biologically-inspired domain.

Shruti Mishra, Abbas Abdolmaleki, Arthur Guez, Piotr Trochim, Doina Precup

CoRR, 2019

An Investigation of Model-Free Planning.

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

Proceedings of the 36th International Conference on Machine Learning, 2019

Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search.

Lars Buesing, Theophane Weber, Yori Zwols, Nicolas Heess, Sébastien Racanière, Arthur Guez, Jean-Baptiste Lespiau

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Learning to Search with MCTSnets.

Arthur Guez, Theophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Rémi Munos, David Silver

Proceedings of the 35th International Conference on Machine Learning, 2018

Adaptive planning in human search.

Moritz Krusche, Eric Schulz, Arthur Guez, Maarten Speekenbrink

Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018

2017

Mastering the game of Go without human knowledge.

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

Nat., 2017

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

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

CoRR, 2017

Imagination-Augmented Agents for Deep Reinforcement Learning.

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

CoRR, 2017

Imagination-Augmented Agents for Deep Reinforcement Learning.

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

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

The Predictron: End-To-End Learning and Planning.

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

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Mastering the game of Go with deep neural networks and tree search.

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

Nat., 2016

Learning functions across many orders of magnitudes.

Hado van Hasselt, Arthur Guez, Matteo Hessel, David Silver

CoRR, 2016

Learning values across many orders of magnitude.

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

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Deep Reinforcement Learning with Double Q-Learning.

Hado van Hasselt, Arthur Guez, David Silver

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Increasing the Action Gap: New Operators for Reinforcement Learning.

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

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2014

Better Optimism By Bayes: Adaptive Planning with Rich Models.

Arthur Guez, David Silver, Peter Dayan

CoRR, 2014

Bayes-Adaptive Simulation-based Search with Value Function Approximation.

Arthur Guez, Nicolas Heess, David Silver, Peter Dayan

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

Scalable and Efficient Bayes-Adaptive Reinforcement Learning Based on Monte-Carlo Tree Search.

Arthur Guez, David Silver, Peter Dayan

J. Artif. Intell. Res., 2013

2012

Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search.

Arthur Guez, David Silver, Peter Dayan

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2010

Multi-tasking SLAM.

Arthur Guez, Joelle Pineau

Proceedings of the IEEE International Conference on Robotics and Automation, 2010

2009

Treating Epilepsy via Adaptive Neurostimulation: a Reinforcement Learning Approach.

Joelle Pineau, Arthur Guez, Robert D. Vincent, Gabriella Panuccio, Massimo Avoli

Int. J. Neural Syst., 2009

2008

Adaptive Treatment of Epilepsy via Batch-mode Reinforcement Learning.

Arthur Guez, Robert D. Vincent, Massimo Avoli, Joelle Pineau

Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008