top of page

Complexity Science

Allen Downey, Olin College
Complexity Science is an approach to modeling systems using tools from discrete mathematics and computer science, including networks, cellular automata, and agent-based models. It has applications in many areas of natural and social science. Python is a particularly good language for exploring and implementing models of complex systems. In this tutorial, I present material from the second edition of *Think Complexity* and from a class I teach at Olin College. We will work with random networks using NetworkX, with cellular automata using NumPy, and we will implement simple agent-based models.


We will use NetworkX and NumPy, but no prior experience with these libraries is required.

bottom of page