A. Guez

发表

Bayes-Adaptive Simulation-based Search with Value Function Approximation

Peter Dayan, David Silver, Nicolas Heess, 2014, NIPS.

Increasing the Action Gap: New Operators for Reinforcement Learning

Marc G. Bellemare, Rémi Munos, Philip S. Thomas, 2015, AAAI.

Learning to Search with MCTSnets

Rémi Munos, Oriol Vinyals, Karen Simonyan, 2018, ICML.

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

Demis Hassabis, Karen Simonyan, David Silver, 2017, ArXiv.

Better Optimism By Bayes: Adaptive Planning with Rich Models pdf

Peter Dayan, David Silver, Arthur Guez, 2014, ArXiv.

Sample-based Search Methods for Bayes-Adaptive Planning

A. Guez, 2015 .

Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search

Peter Dayan, David Silver, Arthur Guez, 2012, NIPS.

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

Peter Dayan, David Silver, Arthur Guez, 2013, J. Artif. Intell. Res..

Deep Reinforcement Learning with Double Q-Learning pdf

David Silver, Arthur Guez, Hado van Hasselt, 2015, AAAI.

A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play

Demis Hassabis, Karen Simonyan, David Silver, 2018, Science.

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

Nicolas Heess, Lars Buesing, Arthur Guez, 2018, ICLR.

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

Demis Hassabis, Koray Kavukcuoglu, David Silver, 2016, Nature.

Imagination-Augmented Agents for Deep Reinforcement Learning

Razvan Pascanu, Demis Hassabis, David Silver, 2017, NIPS.

Mastering the game of Go without human knowledge

Demis Hassabis, Karen Simonyan, Fan Hui, 2017, Nature.

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

Demis Hassabis, Karen Simonyan, David Silver, 2019, Nature.

Learning values across many orders of magnitude

David Silver, Matteo Hessel, Arthur Guez, 2016, NIPS.

Adaptive Treatment of Epilepsy via Batch-mode Reinforcement Learning

Joelle Pineau, Robert D. Vincent, Arthur Guez, 2008, AAAI.

Model-based Bayesian Reinforcement Learning with Adaptive State Aggregation

Doina Precup, A. Guez, Joelle Pineau, 2009 .

Adaptive control of epileptiform excitability in an in vitro model of limbic seizures

Joelle Pineau, Arthur Guez, Gabriella Panuccio, 2013, Experimental Neurology.

CO PTI DICE: O FFLINE C ONSTRAINED R EINFORCE MENT L EARNING VIA S TATIONARY D ISTRIBUTION C ORRECTION E STIMATION

Jongmin Lee, N. Heess, Doina Precup, 2022 .

Retrieval-Augmented Reinforcement Learning

Nan Rosemary Ke, Adrià Puigdomènech Badia, T. Lillicrap, 2022, ICML.

Large-Scale Retrieval for Reinforcement Learning

L. Sifre, T. Lillicrap, A. Guez, 2022, ArXiv.

Muesli: Combining Improvements in Policy Optimization

Ivo Danihelka, L. Sifre, A. Guez, 2021, ICML.

P OLICY IMPROVEMENT BY PLANNING WITH G UMBEL

Ivo Danihelka, A. Guez, Julian Schrittwieser, 2022 .

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

Jessica B. Hamrick, Feryal M. P. Behbahani, A. Guez, 2020, ICLR.

Multi-tasking SLAM

Joelle Pineau, Arthur Guez, A. Guez, 2010, 2010 IEEE International Conference on Robotics and Automation.

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

Tom Schaul, David Silver, Matteo Hessel, 2016, ICML.

COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation

N. Heess, Doina Precup, A. Guez, 2022, ICLR.

Counterfactual Credit Assignment in Model-Free Reinforcement Learning

Marcus Hutter, Nicolas Heess, Fabio Viola, 2020, ICML.

An investigation of model-free planning pdf

Tom Eccles, Laurent Orseau, David Silver, 2019, ICML.

Treating Epilepsy via Adaptive Neurostimulation: a Reinforcement Learning Approach

Joelle Pineau, Robert D. Vincent, Arthur Guez, 2009, Int. J. Neural Syst..

Adaptive planning in human search

Maarten Speekenbrink, Arthur Guez, Eric Schulz, 2018, bioRxiv.

Augmenting learning using symmetry in a biologically-inspired domain pdf

Doina Precup, Abbas Abdolmaleki, Shruti Mishra, 2019, ArXiv.

Optimism and Adaptivity in Policy Optimization

Doina Precup, A. Guez, Tom Zahavy, 2023, arXiv.org.

Large-Scale Retrieval for Reinforcement Learning

L. Sifre, T. Lillicrap, A. Guez, 2022, NeurIPS.

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

Andrew Jaegle, Nicolas Heess, Lars Buesing, 2020, ArXiv.

Physically Embedded Planning Problems: New Challenges for Reinforcement Learning pdf

Andrew Jaegle, Jonathan J. Hunt, Nicolas Heess, 2020, ArXiv.

Policy improvement by planning with Gumbel

Ivo Danihelka, A. Guez, Julian Schrittwieser, 2022, ICLR.

Acceleration in Policy Optimization

Doina Precup, A. Guez, Tom Zahavy, 2023, 2306.10587.

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

Chris J. Maddison, George van den Driessche, Aja Huang, 2016, Nature.

Gemini: A Family of Highly Capable Multimodal Models

Tara N. Sainath, Dalia El Badawy, Reinald Kim Amplayo, 2023, ArXiv.

Gemini: A Family of Highly Capable Multimodal Models

Tara N. Sainath, Dalia El Badawy, Reinald Kim Amplayo, 2023, ArXiv.

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Dalia El Badawy, Nicola De Cao, Charline Le Lan, 2024, ArXiv.