Logo

Think Complexity: Complexity Science and Computational Modeling

Large book cover: Think Complexity: Complexity Science and Computational Modeling

Think Complexity: Complexity Science and Computational Modeling
by

Publisher: Green Tea Press
ISBN/ASIN: 1449314635
Number of pages: 146

Description:
This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science. The 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.

Home page url

Download or read it online for free here:
Download link
(1.2MB, PDF)

Similar books

Book cover: Algorithmic Randomness and ComplexityAlgorithmic Randomness and Complexity
by - Springer
Computability and complexity theory are two central areas of research in theoretical computer science. This book provides a systematic, technical development of algorithmic randomness and complexity for scientists from diverse fields.
(12153 views)
Book cover: Computability and ComplexityComputability and Complexity
- Wikibooks
This book is intended as an introductory textbook in Computability Theory and Complexity Theory, with an emphasis on Formal Languages. Its target audience is CS and Math students with some background in programming and data structures.
(11145 views)
Book cover: Around Kolmogorov Complexity: Basic Notions and ResultsAround Kolmogorov Complexity: Basic Notions and Results
by - arXiv.org
Algorithmic information theory studies description complexity and randomness. This text covers the basic notions of algorithmic information theory: Kolmogorov complexity, Solomonoff universal a priori probability, effective Hausdorff dimension, etc.
(8491 views)
Book cover: Measure-Preserving SystemsMeasure-Preserving Systems
by - University of North Carolina
These notes provide an introduction to the subject of measure-preserving dynamical systems, discussing the dynamical viewpoint; how and from where measure-preserving systems arise; the construction of measures and invariant measures; etc.
(12681 views)