by Allen B. Downey
Buy this book from Amazon.com.
Download this book in PDF.
Read this book online.
This book is about complexity science, data structures and algorithms,
intermediate programming in Python, and the philosophy of science:
- Data structures and algorithms: A data structure is
a collection that contains data elements organized in a way
that supports particular operations. For example, a dictionary
organizes key-value pairs in a way that provides fast
mapping from keys to values, but mapping from values to
keys is generally slower.
An algorithm is a mechanical process for performing a computation.
Designing efficient programs often involves the co-evolution of data
structures and the algorithms that use them. For example, the first
few chapters are about graphs, a data structure that is a good
implementation of a graph---nested dictionaries---and several graph
algorithms that use this data structure.
- Python programming: This book picks up
Python leaves off. I assume that you have read that book or
have equivalent knowledge of Python. As always, I will try to
emphasize fundmental ideas that apply to programming in many
languages, but along the way you will learn some useful features that
are specific to Python.
- Computational modeling: A model is a simplified description
of a system that is useful for simulation or analysis. Computational
models are designed to take advantage of cheap, fast computation.
- Philosophy of science: The models and results in this book
raise a number of questions relevant to the philosophy of science,
including the nature of scientific laws, theory choice,
realism and instrumentalism, holism and reductionism, and Bayesian
This book focuses on discrete models, which include graphs, cellular
automata, and agent-based models. They are often characterized
by structure, rules and transitions rather than by equations.
They tend to be more abstract than continuous models; in some
cases there is no direct correspondence between the model and
a physical system.
Complexity science is an interdisciplinary field---at the
intersection of mathematics, computer science and physics---that
focuses on these kinds of models. That's what this book is about.
This book is under
Commons Attribution-NonCommercial 3.0 Unported License, which means
that you are free to copy, distribute, and modify it, as long as you
attribute the work and don't use it for commercial purposes.
Download the LaTeX source code (with figures and a Makefile)
in a zip file.
Other Free Books by Allen Downey are available from
Green Tea Press.
Like this book?
Are you using one of our books in a class? We'd like to know
about it. Please consider filling out this short survey.
Think Python 2e
Think Stats 2e