Book description
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.
Table of contents
- Preface
- 1. Complexity Science
- 2. Graphs
- 3. Analysis of Algorithms
- 4. Small World Graphs
- 5. Scale-Free Networks
- 6. Cellular Automata
- 7. Game of Life
- 8. Fractals
- 9. Self-Organized Criticality
- 10. Agent-Based Models
- 11. Case Study: Sugarscape
- 12. Case Study: Ant Trails
- 13. Case Study: Directed Graphs and Knots
- 14. Case Study: The Volunteer’s Dilemma
- A. Call for Submissions
- B. Reading List
- Index
- About the Author
- Colophon
- Copyright
Product information
- Title: Think Complexity
- Author(s):
- Release date: March 2012
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781449314637
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