Think Complexity: Complexity Science and Computational ModelingExpand your Python skills by working with data structures and algorithms in a refreshing context—through an eyeopening exploration of complexity science. Whether you’re an intermediatelevel Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of exercises, case studies, and easytounderstand explanations. You’ll work with graphs, algorithm analysis, scalefree 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 selflearners gain valuable experience with topics and ideas they might not encounter otherwise.

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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 
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