Source files for my course on Game Theory.
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Game Theory


This is a course on Game theory. It covers 3 main topics:

  1. Equilibrium computation and Repeated games;
  2. Evolutionary game theory;
  3. Current research topics

The course is taught in an active learning framework with class time being used for activities and demonstrations whilst the content is made available to the students at the start of the course.

Throughout this course concepts are illustrated/demonstrated using Python. In particular the following libraries are used:

  • Nashpy: computation of equilibria.
  • Axelrod: study of the Iterated Prisoner's Dilemma.
  • Sympy: used to verify and carry out symbolic computations.
  • Numpy: used for various linear algebraic calculations.


  • Normal Form Games
  • Nash equilibrium
  • Repeated games
  • Evolutionary game theory
  • Contemporary research


Teaching notes are available here

Contents of this repository

|--- environment.yml  # A conda environment file
|---  # A file to serve the static content
|---  # Tests for
|---  # A file to test the notebooks
|--- assets  # Static files for the course
|--- templates # The various templates for the html
|--- docs  # documentation (notes for the class leader)
|--- nbs  # nbs representing content for the site
     |--- chapters  # Chapters for the course
     |--- exercises  # Exercises for the course
     |--- solutions  # Solutions for the course
     |--- other  # Other information for the course
|--- index.html  # A landing webpage automatically generated by
|--- chapters  # Served content
     |--- 00  # Content directories automatically generated by
     |--- 01
     |--- ...
|--- exercises  # Served content
     |--- 00  # Content directories automatically generated by
     |--- 01
     |--- ...
|--- solutions  # Served content
     |--- 00  # Content directories automatically generated by
     |--- 01
     |--- ...

Serving the content

All the content of the site is written in Jupyter notebooks in the nbs directory. These are used to create .html versions of the content. To generate all the files:

$ inv main

This requires python 3+. An anaconda virtual environment file environment.yml is available.