22 citations · 22 across the 1 of their papers we have counts for
2 papers
cs.LG2019★ 22 cited
Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics
Antonin Raffin, Ashley Hill, René Traoré +3
Scaling end-to-end reinforcement learning to control real robots from vision presents a series of challenges, in particular in terms of sample efficiency. Against end-to-end learni…
cs.LG2018
S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation Learning
Antonin Raffin, Ashley Hill, René Traoré +3
State representation learning aims at learning compact representations from raw observations in robotics and control applications. Approaches used for this objective are auto-encod…