Think Complexity: Complexity Science and Computational ModelingExpand 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.
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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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Think Complexity: Complexity Science and Computational Modeling Allen B. Downey Limited preview - 2012 |
Common terms and phrases
agent-based models agents ants array avalanche behavior BetterMap boids called CCDF cellular automata CHAPTER cluster common complex systems complexity science constant data structure deterministic dictionary directed graph edges elements example Exercise explanation Figure fractal frequency function Gini coefficient graph algorithms grid hashtable implementation initial condition interactions iterator kind knot linear LinearMaps List Comprehensions log-log scale loop maps mathematical matplotlib method named neighbors node number of cells NumPy object 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 self-organized criticality sequence shortest path shows simple simulation small world phenomenon social network step Sugarscape tax rate theory tuple Turing complete Turing machine values vertex Vertex('w vertices volunteering Watts and Strogatz wealth Wikipedia Write a method yield