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.
See tutorial materials here: https://www.scipy2019.scipy.org/tutorial-participant-instructions
See the full SciPy 2019 playlist at https://www.youtube.com/playlist?list=PLYx7XA2nY5GcDQblpQ_M1V3PQPoLWiDAC
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