Game-Theory-and-Python
This is a repository created to run a workshop on Game Theory using the programming language Python and more specifically an open-source software called the Axelrod Python library.
The topics being covered in this workshop are the following:
- An introduction to game theory and the Iterated Prisoner's Dilemma
- Creating matches and tournaments using Axelrod-Python
- Writing strategies and contributing to Axelrod-Python
- Playing against strategies of the Iterated Prisoner's Dilemma
Installing Python
There are various distributions of Python. I recommend using Anaconda which comes packaged with a variety of tools, such as Jupyter Notebooks.
This tutorial is written in Jupyter Notebooks.
Virtual Environment
This repository comes with an environment.yml file. The environment.yml file will allow you to create an Anaconda environment. To do that use the terminal or an anaconda prompt and after you have navigated to the repository just type:
$ conda env create -f environment.yml
The environment can be activated by typing:
$ conda activate game-python
and notebooks can also run in it. To do that you will have to select (from within a running notebook) Kernel and under Change Kernel select the environment game-python.
Usage
The tutorial Game Theory and Python can be used in a workshop environment or through independent learning.
Workshop: The material have been designed for a 2 hours workshop.
Suggested timetable:
- 0:00 - 0:15 Installation (guidelines are given above)
- 0:15 - 0:30 An introduction to game theory and the Iterated Prisoner's Dilemma
- 0:30 - 0:55 Creating matches and tournaments using Axelrod-Python
- 0:55 - 1:20 Writing strategies and contributing to Axelrod-Python
- 1:20 - 1:50 Playing against strategies of the Iterated Prisoner's Dilemma
- 1:50 - 2:00 Closing remarks and wrapping up
In a workshop environment we suggest that the instructor has familiarized themselves with the written parts of the tutorial beforehand. For each notebook it is advised that the instructor gives a mini presentation to the topic followed by them typing out/running the material while the participants follow in their own machines. The instructor should encourage the participants to try the exercises of each notebook alone or with other participants. Before moving to the next notebook the instructor should encourage a discussion amongst everyone regarding the results of the exercises each had and their interpretation.
Independent Learning: An independent learner should aim to spend 2 hour on the material.
Suggested timetable:
- 0:00 - 0:15 Installation (guidelines are given above)
- 0:15 - 0:30 An introduction to game theory and the Iterated Prisoner's Dilemma
- 0:30 - 1:00 Creating matches and tournaments using Axelrod-Python
- 1:00 - 1:30 Writing strategies and contributing to Axelrod-Python
- 1:30 - 2:00 Playing against strategies of the Iterated Prisoner's Dilemma
If the tutorial is being followed by an individual learner, we suggest that the learner reads the written parts of each notebook followed by running the tutorial and completing the exercises. The individual should take some time to reflect on the results of each notebook and their interpretation.
Contributions
All contributions are welcome! This may include communicating ideas for new sections, letting us know about bugs, and code contributions.
Events
This tutorial has been used in the following events:
Have you used this tutorial in an event you hosted or participated? Please do let me know by either contacting me or feel free to open a pr adding your event to this list.
License
The code in this repository, including all code samples in the notebooks listed above, is released under the MIT license.
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