RL research is moving faster than ever before. In order to keep up with the growing trend and ensure that RL research remains reproducible, GenRL aims to aid faster paper reproduction and benchmarking by providing the following main features

PyTorch-first: Modular, Extensible and Idiomatic Python

Tutorials and Documentation: We have over 20 tutorials assuming no knowledge of RL concepts. Basic explanations of algorithms in Bandits, Contextual Bandits, RL, Deep RL, etc.

Unified Trainer and Logging class: code reusability and high-level UI

Ready-made algorithm implementations: ready-made implementations of popular RL algorithms.

Faster Benchmarking: automated hyperparameter tuning, environment implementations, etc.

We want to make RL a more accessible field and would love to hear feedback on how we are doing so far!