Reinforcement Learning

Recent Advances in RL for Continuous Control

A presentation on recent advances in RL, in terms of algorithms, software, and simulators.

Enabling Reinforcement Learning on Real Robots

Invited talk while visiting the INRIA Willow team in Paris.

Ingredients for Learning Locomotion Directly on Real Hardware

Invited talk for the Soccer Robots workshop at Humanoids conference 2024

Designing and Running Real-World RL Experiments

Talk at the Reinforcement Learning for Autonomous Accelerators workshop (RL4AA). 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.

Practical Tips for Reliable Reinforcement Learning

Talk at the CDC 2023 Workshop on Benchmarking, Reproducibility, and Open-Source Code in Controls, about the lessons learned while developping Stable-Baselines3 to have reliable implementations and reproducible experiments.

Knowledge Guided Reinforcement Learning for Robotics

DQN Tutorial

From tabular Q-learning to Deep Q-Network (DQN)

SBX: Stable Baselines Jax

Proof of concept version of Stable-Baselines3 in Jax.

Training RL agents directly on real robots

Presentation on applying Reinforcement Learning directly on real robots

Tutorial: Tools for Robotic Reinforcement Learning

Hands-on RL for Robotics with EAGERx and Stable-Baselines3