# alxndrTL/little-book-rl

The Little Book of Reinforcement Learning

Repository: https://github.com/alxndrTL/little-book-rl
Canonical: https://ross.abutalabs.com/products/little-book-rl
Language: Python
License Family: other
Last push: 2026-07-14T22:43:15+00:00

## Health v2 (maintenance only)
Score: 55/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 92, release rhythm 35, longevity 8
- inputs: {"age_days": 120, "days_push": 50, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, young, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1551, forks 77 (observed 2026-08-28T04:05:02.231320+00:00)

## What it is
The Little Book of Reinforcement Learning is a short introductory book on RL, from basics to applied algorithms, distributed under CC BY-SA 4.0. The repository hosts the book plus supplementary material including PyTorch implementations of algorithms from Monte Carlo methods to PPO and rigorous dynamic programming proofs.

## Use cases
- learn reinforcement learning from scratch
- understand how PPO works with a simple implementation
- find PyTorch code examples of classic RL algorithms
- study proofs of dynamic programming algorithms
- get a short readable intro to RL before reading Sutton & Barto
- implement Monte Carlo and temporal-difference methods in Python

## When to choose
- you want a concise, beginner-friendly introduction to reinforcement learning
- you prefer learning theory alongside minimal PyTorch reference implementations
- you need rigorous supplementary proofs for dynamic programming topics

## When to avoid
- you need a production-ready RL training framework or library
- you want comprehensive coverage of state-of-the-art RL methods beyond PPO
- you need a commercially licensed resource, since the book is CC BY-SA non-commercial in spirit

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, reinforcement-learning, developer-tools
- domain: reinforcement-learning, machine-learning, tutorials, education
- platform: python
- tags: book, pytorch, reinforcement-learning-algorithms, ppo, monte-carlo-methods, dynamic-programming, educational

## Member repositories
- alxndrTL/little-book-rl (main) score 55

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:02.231320+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:30:15.437424+00:00, confidence not recorded.
  - readme: https://github.com/alxndrTL/little-book-rl (fetched 2026-08-28T04:05:02.231320+00:00, sha 6429762d8579)
- Data as of 2026-08-30T08:39:29.467469+00:00.