wtf is little-book-rl?

This repository is the companion page for a short book called The Little Book of Reinforcement Learning. Reinforcement learning is a branch of artificial intelligence where a computer program learns to make decisions by trying actions and getting feedback on how good the results were, rather than being shown labeled examples in advance. The book itself walks through this topic starting from the basics and moving up to algorithms actually used in practice. Alongside the book, the repository holds supporting material. One folder contains Pytorch based code that implements the different algorithms the book covers, ranging from a simple method called Monte Carlo up through a more advanced technique called Proximal Policy Optimization, often shortened to PPO. Another folder holds a separate document with detailed explanations and formal proofs for the dynamic programming algorithms that the book only introduces briefly, written by the author back in 2021. The README notes that a printed copy of the book can be purchased through Amazon, and lists this as version one, released in June 2026. The author says more material may be added to the repository over time. The book is shared under a Creative Commons license, specifically CC BY-SA 4.0, which the README describes as restricted to non-commercial use. This means people can read, share, and build on the material for free, but the license as described here is not meant for commercial purposes. The repository is fairly small and reads more like a companion resource than a full software project. Someone browsing it should expect a readable book plus working code they can run and modify, rather than a polished library meant to be installed as a dependency in other projects.