Think complexity
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 sy...
| Autor principal: | |
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| Otros Autores: | , , |
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, Calif. :
O'Reilly
2012.
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| Edición: | 1st ed |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628146906719 |
Tabla de Contenidos:
- Table of Contents; Preface; Why I Wrote This Book; Suggestions for Teachers; Suggestions for Autodidacts; Contributor List; Conventions Used in This Book; Using Code Examples; Safari® Books Online; How to Contact Us; Chapter 1. Complexity Science; What Is This Book About?; A New Kind of Science; Paradigm Shift?; The Axes of Scientific Models; A New Kind of Model; A New Kind of Engineering; A New Kind of Thinking; Chapter 2. Graphs; What's a Graph?; Representing Graphs; Random Graphs; Connected Graphs; Paul Erdős: Peripatetic Mathematician, Speed Freak; Iterators; Generators
- Chapter 3. Analysis of AlgorithmsOrder of Growth; Analysis of Basic Python Operations; Analysis of Search Algorithms; Hashtables; Summing Lists; pyplot; List Comprehensions; Chapter 4. Small World Graphs; Analysis of Graph Algorithms; FIFO Implementation; Stanley Milgram; Watts and Strogatz; Dijkstra; What Kind of Explanation Is That?; Chapter 5. Scale-Free Networks; Zipf's Law; Cumulative Distributions; Continuous Distributions; Pareto Distributions; Barabási and Albert; Zipf, Pareto, and Power Laws; Explanatory Models; Chapter 6. Cellular Automata; Stephen Wolfram; Implementing CAs
- CADrawerClassifying CAs; Randomness; Determinism; Structures; Universality; Falsifiability; What Is This a Model Of?; Chapter 7. Game of Life; Implementing Life; Life Patterns; Conway's Conjecture; Realism; Instrumentalism; Turmites; Chapter 8. Fractals; Fractal CAs; Percolation; Chapter 9. Self-Organized Criticality; Sand Piles; Spectral Density; Fast Fourier Transform; Pink Noise; Reductionism and Holism; SOC, Causation, and Prediction; Chapter 10. Agent-Based Models; Thomas Schelling; Agent-Based Models; Traffic Jams; Boids; Prisoner's Dilemma; Emergence; Free Will
- Chapter 11. Case Study: SugarscapeThe Original Sugarscape; The Occupy Movement; A New Take on Sugarscape; Pygame; Taxation and the Leave Behind; The Gini Coefficient; Results with Taxation; Conclusion; Chapter 12. Case Study: Ant Trails; Introduction; Model Overview; API Design; Sparse Matrices; wx; Applications; Chapter 13. Case Study: Directed Graphs and Knots; Directed Graphs; Implementation; Detecting Knots; Knots in Wikipedia; Chapter 14. Case Study: The Volunteer's Dilemma; The Prairie Dog's Dilemma; Analysis; The Norms Game; Results; Improving the Chances
- Appendix A. Call for SubmissionsAppendix B. Reading List; Index
