# MathFoundationRL/Book-Mathematical-Foundation-of-Reinforcement-Learning

This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."

Repository: https://github.com/MathFoundationRL/Book-Mathematical-Foundation-of-Reinforcement-Learning
Canonical: https://ross.abutalabs.com/products/book-mathematical-foundation-of-reinforcement-learning
Language: MATLAB
License Family: other
Topics: reinforcement-learning, book, courses, tutorials, artificial-intelligence
Last push: 2026-08-10T06:39:05+00:00

## Health v2 (maintenance only)
Score: 76/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 97, release rhythm 35, longevity 100
- inputs: {"age_days": 1487, "days_push": 23, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 17579, forks 1674 (observed 2026-08-28T04:11:20.010016+00:00)

## What it is
The homepage repository for the book 'Mathematical Foundations of Reinforcement Learning', providing a mathematically rigorous yet accessible introduction to RL concepts and classic algorithms. It includes chapter materials, illustrative grid-world examples, and LaTeX/Beamer slide sources available to instructors on request.

## Use cases
- learn reinforcement learning from a mathematical perspective
- find a beginner-friendly RL textbook requiring only probability and linear algebra
- prepare a university course on reinforcement learning using lecture slides
- understand why classic RL algorithms work, not just how
- study RL fundamentals like Bellman equations, value iteration, and policy gradient
- get a structured self-study path through RL with coherent chapter progression

## When to choose
- you want a rigorous mathematical treatment of RL fundamentals
- you are a senior undergraduate, graduate student, or researcher new to RL
- you need course materials with slides for teaching RL
- you prefer examples grounded in a simple grid world task

## When to avoid
- you need code-first or implementation-heavy RL tutorials
- you want deep learning based RL like deep Q-networks or modern actor-critic methods
- you lack background in probability theory and linear algebra
- you need a software library or tool rather than educational content

## Facets
- artifact type: learning-resource
- maturity: stable
- function: documentation, developer-tools
- domain: reinforcement-learning, artificial-intelligence, machine-learning, tutorials
- platform: cross-platform
- tags: book, slides, latex-beamer, education, mathematics, grid-world-examples

## Member repositories
- MathFoundationRL/Book-Mathematical-Foundation-of-Reinforcement-Learning (main) score 76

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:20.010016+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 2026-08-29T17:02:53.124013+00:00, confidence not recorded.
  - readme: https://github.com/MathFoundationRL/Book-Mathematical-Foundation-of-Reinforcement-Learning (fetched 2026-08-28T04:11:20.010016+00:00, sha de0c18da3dc3)
- Data as of 2026-08-30T08:39:29.467469+00:00.