Complex Systems 530 - Winter 2016

Course repository for CMPLXSYS 530 - Computer Modeling of Complex Systems, taught at the University of Michigan in Winter 2016, providing open-source educational materials for computational complex systems modeling.

Course Overview

An introduction to computational approaches for exploring and modeling complex systems, with primary focus on developing and analyzing agent-based models (ABM). Part of the Complex Systems Graduate Certificate program at University of Michigan.

Course Details

• Instructors: Mike Bommarito and Sarah Cherng
• Schedule: Wednesdays and Fridays, 1:00-2:30 PM ET
• Location: 120 West Hall, University of Michigan
• Term: Winter 2016

Repository Contents

Educational Materials

• Lecture notebooks: Interactive Jupyter notebooks for each topic
• Reading materials: Curated academic papers including:
  • Tocher: “The Art of Simulation”
  • Easley & Kleinberg: “Networks, Crowds, and Markets”
  • Epstein: “Why Model”
  • Gelman & Shalizi: “Philosophy and the Practice of Bayesian Statistics”
• How-to guides: Including GitHub tutorials for students
• Sample code: Examples in Python and NetLogo

Learning Objectives

Students develop competency in:

• Agent-based modeling: Design and implementation
• Programming platforms: Python and NetLogo
• Complex systems concepts: Networks, emergence, adaptation
• Statistical methods: Probability distributions and analysis
• Computational thinking: Model development and validation

Technical Focus

The course emphasizes:

• Building ABMs from scratch
• Network analysis and modeling
• Statistical validation of models
• Computational experimentation
• Reproducible research practices

Open Education Impact

This repository represents a commitment to open education, providing:

• Complete course materials freely available
• Reproducible computational examples
• Foundation for other complex systems courses
• Resource for self-directed learners

Licensed under BSD-2-Clause for maximum educational reuse.