The Beer Game was developed in the 1960s at MIT to illustrate how difficult it is to manage dynamic systems – in this case a supply chain that delivers beer from a brewery to the end consumer.
This repository contains computational notebooks, simulation models and AI training algorithms that explore the game in depth.
Please read the companion blog posts on our website. You can also find a companion slidedeck on slides.com
Have a go at playing the Beer Game (on your own or – much more fun – in a group) before you read the notebooks:
- A single player version of the Beer Game can be found on our website.
- We also have a multiplayer version of the Beer Game set up as a docker container.
The notebooks use the BPTK-Py package, which provides System Dynamics and Agent-based modeling in Python.
- Understanding the Beergame. This is the best place to get started - play the Beer Game in single player mode and learn about the dynamics governing the game. This version uses a System Dynamics implementation of the Beer Game.
- An Agent-based Approach To Modeling the Beer Game. An agent-based simulation of the beergame that can be used to test policies. It is also used as the basis for the reinforcement learning apporach described in the following notebook.
- Training AI to play the Beer Game – A Reinforcement Learning Approach. This notebook introduces the concept of reinforcement learning and then applies it to training intelligent agents to play the Beer Game.
This repository contains two simulation models of the Beer Game - one build using System Dynamics and one built using Agent-based modeling. Both models produce identical results.
The SD version was built with Stella Architect, it can be found in the simulation_models directory. This version of the simulation is used in the Understanding the Beergame notebook.
The ABM version can be found in the src directory. This version is is used in the An Agent-based Approach To Modling the Beergame and Training AI to Play The Beer Game notebooks.
If you have Docker installed (e.g. Docker Desktop on MacOS or on Windows), follow these steps:
- On the command line, move into a directory where you would like to store the Beergame repository.
- Clone the BPTK-Py tutorial repository using git clone: `git clone https://github.com/transentis/beergame.git
- Run
docker-compose up - Point your browser at http://localhost:8888 – this will open JupyterLab showing the contents of your directory.
Alternatively you can install using a Python virtual environment:
- Clone this repo in a directory of your choice:
git clone - Make sure you have python3 installed
- Change into the repo and setup a python venv:
python3 -m venv venv - Activate the venv:
source venv/bin/activate - Install the required modules:
pip install -r requirements.txt - Install the jupyter lab widgets:
jupyter labextension install @jupyter-widgets/jupyterlab-manager - Start jupyter lab:
jupyter lab
Once you have installed, to make sure everything is working open the notebook beergame_abm.ipynb and run all the cells - there should be no error messages and the last graph should look like the one below.
If you have any questions, let us know via email to [email protected].