1 code implementation • 15 Sep 2022 • Steven Kapturowski, Víctor Campos, Ray Jiang, Nemanja Rakićević, Hado van Hasselt, Charles Blundell, Adrià Puigdomènech Badia
The task of building general agents that perform well over a wide range of tasks has been an importantgoal in reinforcement learning since its inception.
no code implementations • 24 Feb 2021 • Víctor Campos, Pablo Sprechmann, Steven Hansen, Andre Barreto, Steven Kapturowski, Alex Vitvitskyi, Adrià Puigdomènech Badia, Charles Blundell
We introduce Behavior Transfer (BT), a technique that leverages pre-trained policies for exploration and that is complementary to transferring neural network weights.
1 code implementation • ICML 2020 • Víctor Campos, Alexander Trott, Caiming Xiong, Richard Socher, Xavier Giro-i-Nieto, Jordi Torres
We perform an extensive evaluation of skill discovery methods on controlled environments and show that EDL offers significant advantages, such as overcoming the coverage problem, reducing the dependence of learned skills on the initial state, and allowing the user to define a prior over which behaviors should be learned.
no code implementations • 12 Nov 2018 • Víctor Campos, Xavier Giro-i-Nieto, Jordi Torres
Evolution Strategies (ES) emerged as a scalable alternative to popular Reinforcement Learning (RL) techniques, providing an almost perfect speedup when distributed across hundreds of CPU cores thanks to a reduced communication overhead.
no code implementations • 21 Mar 2018 • Daniel Fojo, Víctor Campos, Xavier Giro-i-Nieto
Adaptive Computation Time for Recurrent Neural Networks (ACT) is one of the most promising architectures for variable computation.