Antonin Raffin and Ashley Hill

Antonin Raffin and Ashley Hill discuss Stable Baselines past, present and future, State Representation Learning, S-RL Toolbox, RL on real robots, big compute for RL and much more!

Antonin Raffin is a researcher at the German Aerospace Center (DLR) in Munich, working in the Institute of Robotics and Mechatronics. His research is on using machine learning for controlling real robots (because simulation is not enough), with a particular interest for reinforcement learning. 

Ashley Hill is doing his thesis on improving control algorithms using machine learning for real time gain tuning. 
He works mainly with neuroevolution, genetic algorithms, and of course reinforcement learning, applied to mobile robots.  He holds a masters degree in Machine learning, and a bachelors in Computer science from the Université Paris-Saclay. 


Featured References 

stable-baselines on github 
Ashley Hill, Antonin Raffin primary authors. 

S-RL Toolbox 
Antonin Raffin, Ashley Hill, René Traoré, Timothée Lesort, Natalia Díaz-Rodríguez, David Filliat 

Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics 
Antonin Raffin, Ashley Hill, René Traoré, Timothée Lesort, Natalia Díaz-Rodríguez, David Filliat 


Additional References 



TalkRL on Apple Podcasts     TalkRL on Google Podcasts     TalkRL on Spotify    


© 2021 Robin Ranjit Singh Chauhan