# Think Complexity: Complexity Science and Computational Modeling

"O'Reilly Media, Inc.", Mar 2, 2012 - Computers - 142 pages

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 exercises, case studies, and easy-to-understand explanations.

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.

• Work with NumPy arrays and SciPy methods, basic signal processing and Fast Fourier Transform, and hash tables
• Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines
• Get starter code and solutions to help you re-implement and extend original experiments in complexity
• Explore the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, and other topics
• Examine case studies of complex systems submitted by students and readers

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#### Review: Think Complexity: Complexity Science and Computational Modeling

User Review  - Neal Aggarwal - Goodreads

Fabulous book. The example code really gets driven home if you key it all in and struggle to understand the math. There is quite a bit of math here folks, remember that. All can be researched on-line ... Read full review

#### Review: Think Complexity: Complexity Science and Computational Modeling

User Review  - Ray Pace - Goodreads

I found it interesting for a quick thought about some complex problems addessed ina simple model. Read full review

### Contents

 Chapter 1 Complexity Science 1 Chapter 2 Graphs 11 Chapter 3 Analysis of Algorithms 21 Chapter 4 Small World Graphs 37 Chapter 5 ScaleFree Networks 45 Chapter 6 Cellular Automata 57 Chapter 7 Game of Life 73 Chapter 8 Fractals 81
 Chapter 10 AgentBased Models 97 Sugarscape 107 Ant Trails 115 Directed Graphs and Knots 121 The Volunteers Dilemma 125 Appendix A Call for Submissions 131 Appendix B Reading List 133 Index 135

 Chapter 9 SelfOrganized Criticality 87