- Taschenbuch: 263 Seiten
- Verlag: University Press Group Ltd (5. März 2007)
- Sprache: Englisch
- ISBN-10: 0691127026
- ISBN-13: 978-0691127026
- Größe und/oder Gewicht: 15,8 x 1,8 x 23,5 cm
- Durchschnittliche Kundenbewertung: Schreiben Sie die erste Bewertung
- Amazon Bestseller-Rang: Nr. 63.498 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)
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Complex Adaptive Systems: An Introduction to Computational M: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity) (Englisch) Taschenbuch – 5. März 2007
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This book provides the first clear, comprehensive, and accessible account of complex adaptive social systems, by two of the field's leading authorities. Such systems - whether political parties, stock markets, or ant colonies - present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations, "Complex Adaptive Systems" focuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.
"The use of computational, especially agent-based, models has already shown its value in illuminating the study of economic and other social processes. Miller and Page have written an orientation to this field that is a model of motivation and insight, making clear the underlying thinking and illustrating it by varied and thoughtful examples. It conveys with remarkable clarity the essentials of the complex systems approach to the embarking researcher."--Kenneth J. Arrow, winner of the Nobel Prize in economics
"In Complex Adaptive Systems, two masters of this burgeoning field provide a highly readable and novel restatement of the logic of social interactions, linking individually based micro processes to macrosocial outcomes, ranging from Adam Smith's invisible hand to Thomas Schelling's models of standing ovations. The book combines the vision of a new Santa Fe school of computational, social, and behavioral science with essential 'how to' advice for apprentice modelers."--Samuel Bowles, author of Microeconomics: Behavior, Institutions, Evolution
"This is a wonderful book that will be read by graduate students, faculty, and policymakers. The authors write in an extraordinarily clear manner about topics that are very technical and difficult for many people. I sat down to begin thumbing through and found myself deeply engaged."--Elinor Ostrom, author of Understanding Institutional DiversityAlle Produktbeschreibungen
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The book is a great textbook. Its flow of topics is in the correct order to taking the reader from the problem of why this approach is needed, through talking openly about the widespread criticism of this approach and tries answering it in a logical and intelligent way. It then continues to explaining what is a model and how to construct one and off to some examples that show other important corner stones of the field. I couldn't ask for a better arrangement of such book. The book is relatively easy to follow and can be used as an undergraduate textbook or for researchers who look for a good introduction to the field.
Some minor problems that I stumbled upon while reading are as follow: (1) chapter 5 is extremely important as it tries to discuss the approach's criticism, however the arguments wasn't always convincing. Specifically, I would like to see some examples of problems X that are given to the neoclassical theorists, and see some discussions on their inability to deal with them and how this approach can cope with them. (2) The research problems that are introduced are very simple (as also stated by the authors themselves), I think that another chapter with two or three examples of real problems would make this book more valuable for the more knowledgeable readers (e.g. some of Epstein works). (3) After doing a lot of reading on that topic I am still amazed to find new terminology to similar ideas I think the field will mature and be more comprehensive to newcomers if the terminology will be standardize.
Overall, this book provides a great introduction to the field, easy to follow, great arrangement of topics. Highly recommended.
I found this book very readable and the writing style very engaging. The authors ability to keep the subject both intuitive as well as rigorous is quite unique and I rarely read book that are as well balanced. The approach is generally to force people to look at repurcussions and then think about the dynamics that brings them about, which is a lot more sensible than working through from initial conditions the evolution of nonlinear dynamical systems. This approach is contained to examples where one builds the examples and interactive dynamics of the agents themselves rather than for arbitrary chaotic systems.
This book though is not 5 stars to me as I dont like the way it was organized. The beginning of the book was hard for me to figure out what they were talking about or who they were trying to convince. The writing was good, but I was unable to gain insight into the systems they eventually were leading the reader to consider. I finally understood what they were talking about when they mentioned sugarworld which I was familiar with. At that point, in hindsight the beginning of the book made more sense. All in all my only criticism is the conclusion type arguments about the utility of the methods before discussing an elementary example was probably unecessary. I think it would have been better start to finish by starting with examples, building up the difficulty (which they did, but just a fair way into the book) and really reinforcing the merit of the approach (which i found self revealing) at the end rather than the beginning.
There is one thing that I was not pleased. The information provided is too thoretical. Although the provided examples are well articulated they lack real world sense and practical information. I have also read The Perfect Swarm: The Science of Complexity in Everyday Life which seems to have more real life examples and more practical information on the subject but reading this book helped me understand the Perfect Swarm better.
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