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Sep 14, 2022
Geoffrey Cideron, Sertan Girgin, Anton Raichuk, Olivier Pietquin, Olivier Bachem, Léonard Hussenot

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Scalable Deep Reinforcement Learning Algorithms for Mean Field Games


Mar 22, 2022
Mathieu Laurière, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Pérolat, Romuald Élie, Olivier Pietquin, Matthieu Geist

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RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning


Nov 04, 2021
Sabela Ramos, Sertan Girgin, Léonard Hussenot, Damien Vincent, Hanna Yakubovich, Daniel Toyama, Anita Gergely, Piotr Stanczyk, Raphael Marinier, Jeremiah Harmsen, Olivier Pietquin, Nikola Momchev

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* https://github.com/google-research/rlds 

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Continuous Control with Action Quantization from Demonstrations


Oct 19, 2021
Robert Dadashi, Léonard Hussenot, Damien Vincent, Sertan Girgin, Anton Raichuk, Matthieu Geist, Olivier Pietquin

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Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulation


Jun 24, 2021
C. Daniel Freeman, Erik Frey, Anton Raichuk, Sertan Girgin, Igor Mordatch, Olivier Bachem

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* 9 pages + 12 pages of appendices and references. In submission at NeurIPS 2021 Datasets and Benchmarks Track 

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What Matters for Adversarial Imitation Learning?


Jun 01, 2021
Manu Orsini, Anton Raichuk, Léonard Hussenot, Damien Vincent, Robert Dadashi, Sertan Girgin, Matthieu Geist, Olivier Bachem, Olivier Pietquin, Marcin Andrychowicz

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Hyperparameter Selection for Imitation Learning


May 25, 2021
Leonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Lukasz Stafiniak, Sertan Girgin, Raphael Marinier, Nikola Momchev, Sabela Ramos, Manu Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin

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* ICML 2021 

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What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study


Jun 10, 2020
Marcin Andrychowicz, Anton Raichuk, Piotr Stańczyk, Manu Orsini, Sertan Girgin, Raphael Marinier, Léonard Hussenot, Matthieu Geist, Olivier Pietquin, Marcin Michalski, Sylvain Gelly, Olivier Bachem

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