Think Complexity: Complexity Science and Computational Modeling, 2nd Edition

Expand your Python skills by working with data structures and algorithms in a refreshing context—through an eye-opening exploration of complexity science. Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of worked examples, exercises, case studies, and easy-to-understand explanations.

In this updated second edition, you’ll work with graphs, algorithm analysis, scale-free networks, and cellular automata, using advanced features that make Python such a powerful language. Ideal as a text for courses on Python programming and algorithms, Think Complexity will also help self-learners gain valuable experience with topics and ideas they might not encounter otherwise.

For every chapter, there are two Jupyter notebooks in the book’s software repository: one contains the code from the chapter, explanatory text, and exercises; the other contains the solutions to the exercises.

Table of Contents

Chapter 1. Complexity Science
Chapter 2. Graphs
Chapter 3. Small World Graphs
Chapter 4. Scale-Free Networks
Chapter 5. Cellular Automatons
Chapter 6. Game Of Life
Chapter 7. Physical Modeling
Chapter 8. Self-Organized Criticality
Chapter 9. Agent-Based Models
Chapter 10. Herds, Flocks, And Traffic Jams
Chapter 11. Evolution
Chapter 12. Evolution Of Cooperation