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Book
Computational Modeling and Complexity Science
"This book is about data structures and algorithms, intermediate programming in Python, complexity science and the philosophy of science"
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| Added | 14 Feb 2009 |
| Updated | 14 Feb 2009 |
| Authors | Allen B. Downey |
1.1 What’s a graph?
1.2 Representing graphs
1.3 Random graphs
1.4 Connected graphs
1.5 Paul Erd?os: peripatetic mathematician, speed freak
1.6 Iterators
1.7 Generators
2.1 Order of growth
2.2 Analysis of basic operations
2.3 Analysis of search algorithms
2.4 Hashtables
2.5 Summing lists
2.6 List comprehensions
3.1 Analysis of graph algorithms
3.2 FIFO implementation
3.3 Stanley Milgram
3.4 Watts and Strogatz
3.5 Dijkstra
3.6 What kind of explanation is that?
4.1 Zipf’s Law
4.2 Cumulative distributions
4.3 Closed-form distributions
4.4 Pareto distributions
4.5 Barab´asi and Albert
4.6 Zipf, Pareto and power laws
5.1 Wolfram
5.2 Implementing CAs
5.3 Classifying CAs
5.4 Randomness
5.5 Determinism
5.6 Structures
5.7 Universality
5.8 Falsifiability
5.9 What is this a model of?
6.1 Abstract classes
6.2 Conway
6.3 Life patterns
6.4 Conway’s conjecture
6.5 Realism
6.6 Instrumentalism
6.7 Turmites
6.8 Percolation
7.1 Bak, Tang and Wiesenfeld
7.2 Spectral density
7.3 Fast Fourier Transform
7.4 Pink noise
7.5 Forest fire models
7.6 Reductionism and Holism
7.7 SOC, causation and prediction
8.1 Schelling
8.2 Agent-based models
8.3 Traffic jams
8.4 Boids
8.5 Ants
8.6 Sugarscape
8.7 Emergence
9.1 Monty Hall
9.2 Poincar´e
9.3 Streaks and hot spots
9.4 Bayes’ theorem
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