Think Complexity: Complexity Science and Computational Modeling

Description

Enhances Python skills by working with data structures and algorithms and gives examples of complex systems using exercises, case studies, and simple explanations. Table of Contents Preface Why I Wrote This Book Suggestions for Teachers Suggestions for Autodidacts Contributor List Conventions Used in This Book Using Code Examples Safari® Books Online How to Contact Us Chapter 1. Complexity Science What Is This Book About? A New Kind of Science Paradigm Shift? The Axes of Scientific Models A New Kind of Model A New Kind of Engineering A New Kind of Thinking Chapter 2. Graphs What’s a Graph? Representing Graphs Random Graphs Connected Graphs Paul Erdős: Peripatetic Mathematician, Speed Freak Iterators Generators Chapter 3. Analysis of Algorithms Order of Growth Analysis of Basic Python Operations Analysis of Search Algorithms Hashtables Summing Lists pyplot List Comprehensions Chapter 4. Small World Graphs Analysis of Graph Algorithms FIFO Implementation Stanley Milgram Watts and Strogatz Dijkstra What Kind of Explanation Is That? Chapter 5. Scale-Free Networks Zipf’s Law Cumulative Distributions Continuous Distributions Pareto Distributions Barabási and Albert Zipf, Pareto, and Power Laws Explanatory Models Chapter 6. Cellular Automata Stephen Wolfram Implementing CAs CADrawer Classifying CAs Randomness Determinism Structures Universality Falsifiability What Is This a Model Of? Chapter 7. Game of Life Implementing Life Life Patterns Conway’s Conjecture Realism Instrumentalism Turmites Chapter 8. Fractals Fractal CAs Percolation Chapter 9. Self-Organized Criticality Sand Piles Spectral Density Fast Fourier Transform Pink Noise Reductionism and Holism SOC, Causation, and Prediction Chapter 10. Agent-Based Models Thomas Schelling Agent-Based Models Traffic Jams Boids Prisoner’s Dilemma Emergence Free Will Chapter 11. Case Study: Sugarscape The Original Sugarscape The Occupy Movement A New Take on Sugarscape Pygame Taxation and the Leave Behind The Gini Coefficient Results with Taxation Conclusion Chapter 12. Case Study: Ant Trails Introduction Model Overview API Design Sparse Matrices wx Applications Chapter 13. Case Study: Directed Graphs and Knots Directed Graphs Implementation Detecting Knots Knots in Wikipedia Chapter 14. Case Study: The Volunteer’s Dilemma The Prairie Dog’s Dilemma Analysis The Norms Game Results Improving the Chances Appendix A. Call for Submissions Appendix B. Reading List Index