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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Review: Think Complexity: Complexity Science and Computational Modeling
User Review  Franck Chauvel  GoodreadsI am disappointing by this book. I see it more like a study guide with a lot's of external resources to fetch and read (scientific publications or wikipedia articles) as well as programming exercises ... Read full review
Review: Think Complexity: Complexity Science and Computational Modeling
User Review  Neal Aggarwal  GoodreadsFabulous 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 online ... 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 
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Other editions  View all
Think Complexity: Complexity Science and Computational Modeling Allen B. Downey Limited preview  2012 