Search Results for author: Abe Friesen

Found 2 papers, 1 papers with code

Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach

no code implementations • 21 Apr 2022 • Bobak Shahriari, Abbas Abdolmaleki, Arunkumar Byravan, Abe Friesen, SiQi Liu, Jost Tobias Springenberg, Nicolas Heess, Matt Hoffman, Martin Riedmiller

Actor-critic algorithms that make use of distributional policy evaluation have frequently been shown to outperform their non-distributional counterparts on many challenging control tasks.

Continuous Control reinforcement-learning +1

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Acme: A Research Framework for Distributed Reinforcement Learning

3 code implementations • 1 Jun 2020 • Matthew W. Hoffman, Bobak Shahriari, John Aslanides, Gabriel Barth-Maron, Nikola Momchev, Danila Sinopalnikov, Piotr Stańczyk, Sabela Ramos, Anton Raichuk, Damien Vincent, Léonard Hussenot, Robert Dadashi, Gabriel Dulac-Arnold, Manu Orsini, Alexis Jacq, Johan Ferret, Nino Vieillard, Seyed Kamyar Seyed Ghasemipour, Sertan Girgin, Olivier Pietquin, Feryal Behbahani, Tamara Norman, Abbas Abdolmaleki, Albin Cassirer, Fan Yang, Kate Baumli, Sarah Henderson, Abe Friesen, Ruba Haroun, Alex Novikov, Sergio Gómez Colmenarejo, Serkan Cabi, Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, Andrew Cowie, Ziyu Wang, Bilal Piot, Nando de Freitas

These implementations serve both as a validation of our design decisions as well as an important contribution to reproducibility in RL research.

DQN Replay Dataset reinforcement-learning +1

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