Name: Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity) (en Inglés)
Price: 41900.00 CLP
Availability: InStock
Author: Miller, John H. ; Page, Scott
ISBN: 9780691127026

portada Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity) (en Inglés)

Formato

Libro Físico

Autor

John H. Miller

Scott Page

Editorial

Princeton University Press

Año

2007

Idioma

Inglés

N° páginas

288

Encuadernación

Tapa Blanda

Dimensiones

23.5 x 15.8 x 1.8 cm

Peso

0.42 kg.

ISBN

0691127026

ISBN13

9780691127026

Categorías

Cibernética y teoría de sistemas
Sociología

Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity) (en Inglés)

John H. Miller (Autor) · Scott Page (Autor) · Princeton University Press · Tapa Blanda

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Reseña del libro "Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity) (en Inglés)"

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.