Complexity Science | Tutorials
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, we present material from the draft second edition of Think Complexity, and from a class we 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.
Allen Downey
Allen Downey is a professor of computer science at Olin College, a new engineering college near Boston with the mission to fix engineering education. He is the author of Think Python, Think Stats, Think Bayes, Think Complexity, and several other books all available under free licenses.
Jason Woodard
Jason Woodard is an associate professor of engineering and entrepreneurship at Olin College. He studied complex systems and computational modeling at the Santa Fe Institute, and uses complexity science to model the evolution of technology and markets.
Room 9
Wednesday, 17th May, 13:20 - 16:40
