Think Complexity: Exploring Complexity Science with Python

Title

Think Complexity: Exploring Complexity Science with Python

Authors

Files

Link to Full Text

Download Full Text

Contributors

Allen B. Downey - Author

Description

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 where Think 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 epistemology. 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.

Subject 1

Computer Science

ISBN13

9.78E+12

Publisher

Green Tea Press

Resources

Open Textbook Library

License

Attribution-NonCommercial-ShareAlike

Think Complexity: Exploring Complexity Science with Python

Share

COinS