The GitHub repository for 'The Little Book of Reinforcement Learning' offers a concise introduction to the field, covering fundamental concepts and applied algorithms.

Accompanying the book are supplementary materials, including PyTorch implementations of various algorithms, from Monte Carlo to Proximal Policy Optimization (PPO), located in the 'algos/' folder. The 'supplementary/' folder provides in-depth explanations and proofs for dynamic programming algorithms that are briefly touched upon in the book. This resource was initially compiled in 2021 and is expected to be updated with more material.

The book is available for personal printing and is distributed under a non-commercial Creative Commons license (CC BY-SA 4.0). The first version (V1) was released in June 2026.