Designing and Running Real-World RL Experiments: Antonin Raffin
Speaker: Antonin Raffin, Research Engineer in Robotics and Machine Learning, German Aerospace Center (DLR)
Talk Title: Designing and Running Real-World RL Experiments
Abstract: This talk covers the challenges and best practices for designing and running real-world reinforcement learning (RL) experiments. The idea is to walk through the different steps of RL experimentation (task design, choosing the right algorithm, implementing safety layers) and also provide practical advice on how to run experiments and troubleshoot common problems.
Bio: Antonin Raffin is a research engineer in robotics and machine learning at the German Aerospace Center (DLR). Previously, he worked on state representation learning in the ENSTA robotics lab (U2IS), where he created the Stable-Baselines library together with Ashley Hill. His research focus is now on applying reinforcement learning directly to real robots, for which he continues to maintain the Stable-Baselines3 library
Slides: https://araffin.github.io/slides/bu-d...
Alternate Recording: • Designing and Running Real World RL Experi...