Think Complexity

Author: Allen Downey
Publisher: "O'Reilly Media, Inc."
ISBN: 1492040150
Size: 25.81 MB
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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.

Think Complexity

Author: Allen B. Downey
Publisher:
ISBN:
Size: 21.77 MB
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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 fundamental 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.

Computation In Science

Author: Konrad Hinsen
Publisher: Morgan & Claypool Publishers
ISBN: 1681740931
Size: 73.80 MB
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This book provides a theoretical background in computation to scientists who use computational methods. It explains how computing is used in the natural sciences, and provides a high-level overview of those aspects of computer science and software engineering that are most relevant for computational science. The focus is on concepts, results, and applications, rather than on proofs and derivations. The unique feature of this book is that it “connects the dots between computational science, the theory of computation and information, and software engineering. The book should help scientists to better understand how they use computers in their work, and to better understand how computers work. It is meant to compensate a bit for the general lack of any formal training in computer science and information theory. Readers will learn something they can use throughout their careers.

Generative Emergence

Author: Benyamin B. Lichtenstein
Publisher: Oxford University Press (UK)
ISBN: 0199933596
Size: 74.97 MB
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'Generative Emergence' provides insight into the non-linear dynamics that lead to organizational emergence through the use of complexity sciences. The book explores how the model of generative emergence could be applied to enact emergence within and across organizations.

Organisation And Complexity

Author: Jacco van Uden
Publisher: Universal-Publishers
ISBN: 9781581122220
Size: 75.68 MB
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Students of organisation have used complexity theory in many different ways and for many different reasons. What characterises the writings of most 'management thinkers', however, is that the authors are primarily concerned with the question of "how to make this complexity thing work for us?" This study takes a rather different approach. Ideas and concepts of the science of complexity are borrowed to develop the idea that organisations live lives of their own - an idea that is very much at odds with the dominant view that understands organisations as tools that we use to realise certain goals. To illustrate matters, the book discusses the developments of the organisation of Vitesse, a mediocre Dutch professional football club that according to its president needed to be transformed into a major player in the family entertainment industry.

Sociology And Complexity Science

Author: Brian Castellani
Publisher: Springer Science & Business Media
ISBN: 3540884629
Size: 13.12 MB
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By now, most academics have heard something about the new science of complexity. In a manner reminiscent of Einstein and the last hundred years of physics, complexity science has captured the public imagination. ® One can go to Amazon. com and purchase books on complexification (Casti 1994), emergence (Holland 1998), small worlds (Barabási 2003), the web of life (Capra 1996), fuzzy thinking (Kosko 1993), global c- plexity (Urry 2003) and the business of long-tails (Anderson 2006). Even television has incorporated the topics of complexity science. Crime shows ® ® such as 24 or CSI typically feature investigators using the latest advances in computational modeling to “simulate scenarios” or “data mine” all p- sible suspects—all of which is done before the crime takes place. The ® World Wide Web is another example. A simple search on Google. Com using the phrase “complexity science” gets close to a million hits! C- plexity science is ubiquitous. What most scholars do not realize, however, is the remarkable role sociologists are playing in this new science. C- sider the following examples. 0. 1 Sociologists in Complexity Science The first example comes from the new science of networks (Barabási 2003). By now, most readers are familiar with the phenomena known as six-degrees of separation—the idea that, because most large networks are comprised of a significant number of non-random weak-ties, the nodes (e. g. , people, companies, etc.

Thinking Complexity

Author: Paul Cilliers
Publisher: Isce Pub
ISBN:
Size: 50.74 MB
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This volume examines the impact of complexity theory on various disciplines, especially the area of philosophy. (Philosophy)

Think Python

Author: Allen B. Downey
Publisher: CreateSpace
ISBN: 9781441419163
Size: 79.55 MB
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Python for Software Design is a concise introduction to software design using the Python programming language. Intended for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. The focus is on the programming process, with special emphasis on debugging. The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practice each new concept. Exercise solutions and code examples are available from thinkpython.com, along with Swampy, a suite of Python programs that is used in some of the exercises. ** Published under the terms of the GNU Free Documentation License. Money raised from the sale of this book supports the development of free software and documentation.

The Sage Handbook Of Complexity And Management

Author: Peter Allen
Publisher: SAGE
ISBN: 1446209741
Size: 26.15 MB
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The SAGE Handbook of Complexity and Management is the first substantive scholarly work to provide a map of the state of art research in the growing field emerging at the intersection of complexity science and management studies. Edited and written by internationally respected scholars from management and related disciplines, the Handbook will be the definitive reference source for understanding the implications of complexity science for management research and practice. Part One: Foundations introduces complexity science and its implications for the foundations of scientific knowledge, including management knowledge. Part Two: Applications presents the numerous ways in which complexity science models and tools, as well as complexity thinking, are being applied to management and organizational phenomena and the insights gained as a result. Part Three: Interfaces highlights how complexity science is transforming various non-management fields and, in so doing, creating exciting interfaces for bridging between management and related disciplines.

How To Think Like A Computer Scientist

Author: Allen B. Downey
Publisher: CreateSpace
ISBN: 9781441419057
Size: 38.16 MB
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HOW TO THINK LIKE A COMPUTER SCIENTIST. * Published under the terms of the GNU Free Documentation License. Money raised from the sale of this book supports the development of free software and documentation.