Think Complexity

Complexity Science and Computational Modeling

by Allen Downey

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Book Description

Complexity science uses computation to explore the physical and social sciences. In Think Complexity, you'll use graphs, cellular automata, and agent-based models to study topics in physics, biology, and economics.

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 worked examples, exercises, case studies, and easy-to-understand explanations.

In this updated second edition, you will: Work with NumPy arrays and SciPy methods, including basic signal processing and Fast Fourier Transform; Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines; Get Jupyter notebooks filled with starter code and solutions to help you re-implement and extend original experiments in complexity; and models of computation like Turmites, Turing machines, and cellular automata; Explore the philosophy of science, including the nature of scientific laws, theory choice, and realism and instrumentalism.

Ideal as a text for a course on computational modeling in Python, Think Complexity also helps self-learners gain valuable experience with topics and ideas they might not encounter otherwise.

This open book is licensed under a Creative Commons License (CC BY-NC-SA). You can download Think Complexity ebook for free in PDF format (6.6 MB).

Table of Contents

Chapter 1
Complexity Science
Chapter 2
Chapter 3
Small World Graphs
Chapter 4
Scale-free networks
Chapter 5
Cellular Automatons
Chapter 6
Game of Life
Chapter 7
Physical modeling
Chapter 8
Self-organized criticality
Chapter 9
Agent-based models
Chapter 10
Herds, Flocks, and Traffic Jams
Chapter 11
Chapter 12
Evolution of cooperation
A Reading list

Book Details

Computer Science
O'Reilly Media, Green Tea Press
ISBN13 Digital
ISBN10 Digital
PDF Size
6.6 MB

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