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Learning Compositional Neural Programs for Continuous Control

Jul 27, 2020
Thomas Pierrot, Nicolas Perrin, Feryal Behbahani, Alexandre Laterre, Olivier Sigaud, Karim Beguir, Nando de Freitas


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Acme: A Research Framework for Distributed Reinforcement Learning

Jun 01, 2020
Matt Hoffman, Bobak Shahriari, John Aslanides, Gabriel Barth-Maron, Feryal Behbahani, Tamara Norman, Abbas Abdolmaleki, Albin Cassirer, Fan Yang, Kate Baumli, Sarah Henderson, Alex Novikov, Sergio Gómez Colmenarejo, Serkan Cabi, Caglar Gulcehre, Tom Le Paine, Andrew Cowie, Ziyu Wang, Bilal Piot, Nando de Freitas


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Privileged Information Dropout in Reinforcement Learning

May 19, 2020
Pierre-Alexandre Kamienny, Kai Arulkumaran, Feryal Behbahani, Wendelin Boehmer, Shimon Whiteson


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Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation

Dec 18, 2019
Tianhong Dai, Kai Arulkumaran, Samyakh Tukra, Feryal Behbahani, Anil Anthony Bharath


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Modular Meta-Learning with Shrinkage

Sep 12, 2019
Yutian Chen, Abram L. Friesen, Feryal Behbahani, David Budden, Matthew W. Hoffman, Arnaud Doucet, Nando de Freitas

* 14 pages (4 main, 8 supplement), under review 

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Learning from Demonstration in the Wild

Nov 08, 2018
Feryal Behbahani, Kyriacos Shiarlis, Xi Chen, Vitaly Kurin, Sudhanshu Kasewa, Ciprian Stirbu, João Gomes, Supratik Paul, Frans A. Oliehoek, João Messias, Shimon Whiteson

* 8 pages, 6 figures 

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