Think Complexity
Complexity Science and Computational Modeling
by Allen Downey
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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. 
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
Preface
Chapter 1
Complexity Science
Chapter 2
Graphs
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
Evolution
Chapter 12
Evolution of cooperation
A Reading list
Book Details
Title
Think Complexity
Subject
Computer Science
Publisher
O'Reilly Media, Green Tea Press
Published
2018
Pages
228
Edition
2
Language
English
ISBN13 Digital
9781492040200
ISBN10 Digital
1492040207
PDF Size
6.6 MB
License
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