Slides for MIT Press textbook "Multi-Agent Reinforcement Learning: Foundations and Modern Approaches"

This repository contains slides for the MIT Press textbook "Multi-Agent Reinforcement Learning: Foundations and Modern Approaches" by Stefano V. Albrecht, Filippos Christianos, and Lukas Schäfer.

The book can be freely accessed on this webpage: www.marl-book.com

The slides are written in LaTeX with beamer (for a quick introduction to beamer, see this Overleaf Beamer quickstart guide and this five-part tutorial). We provide all compiled .pdf files for the slides, as well as the source files of all assets and .tex files in /source. We recommend compiling with xelatex. In the source/preamble.tex file, we define useful commands and import packages that are used throughout the slides.

The slides use the metropolis theme, which is a modern, simple and clean theme for LaTeX beamer. The theme can be found on Github and Overleaf. Note: for best results, the Fira Sans and Fire Mono fonts should be installed on your system. See the metropolis theme documentation for more details.

Using the slides in your class/lectures

Instructors who want to use the slides in their lectures are free to make changes (e.g. remove or add materials as required) by using the provided source files. However, please do include a credit line to mention the book and book authors, and include a link to the original slides.

If you use the book or slides in your class, please let us know and we will add your class and institution to a list that will be published here.

Reporting issues and proposing improvements

If you spot any typos or errors in the slides, please report them to us by creating an Issue here on Github.

Similarly, if you have made improvements to the slides, consider creating a pull request to incorporate your improvements to the files on this page.