# ShangtongZhang/reinforcement-learning-an-introduction

Python Implementation of Reinforcement Learning: An Introduction

Repository: https://github.com/ShangtongZhang/reinforcement-learning-an-introduction
Canonical: https://ross.abutalabs.com/products/reinforcement-learning-an-introduction
Language: Python
License: MIT
License Family: permissive
Topics: reinforcement-learning, artificial-intelligence
Last push: 2024-08-09T01:09:15+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3641, "days_push": 755, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 14756, forks 4959 (observed 2026-08-28T04:11:07.641294+00:00)

## What it is
Python implementations of the figures and examples from Sutton & Barto's 'Reinforcement Learning: An Introduction' (2nd Edition). It serves as a code companion to the textbook, replicating bandit algorithms, dynamic programming, Monte Carlo, and temporal-difference learning results.

## Use cases
- study reinforcement learning alongside Sutton & Barto's book
- see working Python code for bandit and gridworld examples
- reproduce textbook figures like epsilon-greedy and UCB curves
- learn dynamic programming and Monte Carlo methods by example
- find reference implementations of TD learning algorithms

## When to choose
- you are reading the Sutton & Barto textbook and want matching code
- you want simple, educational implementations rather than a heavy RL framework
- you need to reproduce the book's figures for study or teaching

## When to avoid
- you need a production RL training library with GPU support
- you want modern deep RL algorithms like PPO or SAC
- you need exercise solutions for the book

## Facets
- artifact type: learning-resource
- maturity: stable
- function: reinforcement-learning, machine-learning, data-visualization
- domain: reinforcement-learning, artificial-intelligence, machine-learning, tutorials
- platform: python, cross-platform
- tags: sutton-barto, educational, book-companion, python-implementations, figures

## Member repositories
- ShangtongZhang/reinforcement-learning-an-introduction (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:07.641294+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 2026-08-29T17:07:12.317247+00:00, confidence not recorded.
  - readme: https://github.com/ShangtongZhang/reinforcement-learning-an-introduction (fetched 2026-08-28T04:11:07.641294+00:00, sha a03f0eb37a46)
- Data as of 2026-08-30T08:39:29.467469+00:00.