Think complexity: complexity science and computational modeling

Complexity science uses computation to explore the physical and social sciences. In Think Complexity, you'll use graphs, cellular automata, and agent-based models to study topics in physics, biology, and economics. 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 will: Work with NumPy arrays and SciPy methods, including basic signal processing and Fast Fourier Transform, Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines, Get Jupyter notebooks filled with starter code and solutions to help you re-implement and extend original experiments in complexity; and models of computation like Turmites, Turing machines, and cellular automata, Explore the philosophy of science, including the nature of scientific laws, theory choice, and realism and instrumentalism. Ideal as a text for a course on computational modeling in Python, Think Complexity also helps self-learners gain valuable experience with topics and ideas they might not encounter otherwise. --Back cover.

Chapter 3. Small World GraphsStanley Milgram ; Watts and Strogatz ; Ring Lattice ; WS Graphs ; Clustering ; Shortest Path Lengths ; The WS Experiment ; What Kind of Explanation Is That? ; Breadth-First Search ; Dijkstra's Algorithm ; Exercises ; Chapter 4. Scale-Free Networks ; Social Network Data ; WS Model ; Degree ; Heavy-Tailed Distributions ; Barabási-Albert Model ; Generating BA Graphs ; Cumulative Distributions ; Explanatory Models ; Exercises ; Chapter 5. Cellular Automatons ; A Simple CA ; Wolfram's Experiment ; Classifying CAs ; Randomness ; Determinism ; Spaceships ; Universality ; Falsifiability

Chapter 9. Agent-Based ModelsSchelling's Model ; Implementation of Schelling's Model ; Segregation ; Sugarscape ; Wealth Inequality ; Implementing Sugarscape ; Migration and Wave Behavior ; Emergence ; Exercises ; Chapter 10. Herds, Flocks, and Traffic Jams ; Traffic Jams ; Random Perturbation ; Boids ; The Boid Algorithm ; Arbitration ; Emergence and Free Will ; Exercises ; Chapter 11. Evolution ; Simulating Evolution ; Fitness Landscape ; Agents ; Simulation ; No Differentiation ; Evidence of Evolution ; Differential Survival ; Mutation ; Speciation ; Summary ; Exercises ; C…