67 citations · 138 across the 9 of their papers we have counts for
3 papers · 1 filter
Distilled Domain Randomization
Julien Brosseit, Benedikt Hahner, Fabio Muratore +2
Deep reinforcement learning is an effective tool to learn robot control policies from scratch. However, these methods are notorious for the enormous amount of required training dat…
Robot Learning from Randomized Simulations: A Review
Fabio Muratore, Fabio Ramos, Greg Turk +3
The rise of deep learning has caused a paradigm shift in robotics research, favoring methods that require large amounts of data. Unfortunately, it is prohibitively expensive to gen…
An Empirical Analysis of Measure-Valued Derivatives for Policy Gradients
João Carvalho, Davide Tateo, Fabio Muratore +1
Reinforcement learning methods for robotics are increasingly successful due to the constant development of better policy gradient techniques. A precise (low variance) and accurate…