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
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 
135  
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Common terms and phrases
agentbased models agents analysis ants array avalanche behavior BetterMap boids called CCDF cellular automata cluster coefficient common complex systems complexity science constant data structure def __init__(self deterministic dictionary directed graph edges elements example Exercise explanation Figure fractal frequency function graph algorithms grid hashtable implementation initial condition interactions iterator kind knot linear LinearMaps List Comprehensions loglog scale longtailed distributions loop maps mathematical matplotlib method named neighbors node number of cells NumPy order of growth parameters Pareto distribution path lengths patterns pheromone player plot probability problem pyplot Python queue random graphs realistic regular graph result rules runtime sand pile Schelling’s model selforganized criticality sequence shortest path shows simple simulation small world phenomenon social network step Sugarscape theory tuple Turing complete Turing machine values vertex vertices volunteering Watts and Strogatz wealth Wikipedia Wolfram Write a method yield