Open RL Benchmark


OpenRLBenchmark is a collaborative project aimed at advancing the field of reinforcement learning. It provides a comprehensive benchmark suite that covers a wide range of tasks, domains, and difficulties, enabling researchers and practitioners to fairly compare algorithms. The project utilizes the tracking tool Weights & Biases to provide a centralized location for storing and visualizing experiment data, making it easier for users to access and analyze results.

The project invites researchers, practitioners, and enthusiasts to contribute their algorithms, results, and insights, creating a unique opportunity for collaboration and the exchange of information. It serves as a valuable tool for advancing the field of reinforcement learning and facilitating the reproducibility of results.

OpenRLBenchmark offers a platform for the advancement of the field of reinforcement learning, where individuals can contribute their experiments and access experiments from others.

Quentin Gallouédec
Quentin Gallouédec
Ph.D. Student in Reinforcement Learning

I mainly focus on the design of robust reinforcement learning algorithms, especially for highly sparse reward environments.