Quantitative Sociodynamics: Stochastic Methods and Models of Social Interaction Processes (Theory and Decision Library B)

Helbing, Dirk

ISBN 10: 0792331923 / ISBN 13: 9780792331926

Published by Kluwer Academic Publishers, 1995

About this Item

This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,800grams, ISBN:9780792331926.

Seller Inventory # 8246324

Bibliographic Details

• Title: Quantitative Sociodynamics: Stochastic Methods and Models of Social Interaction Processes (Theory and Decision Library B)
• Publisher: Kluwer Academic Publishers
• Publication Date: 1995
• Language: English
• ISBN 10: 0792331923
• ISBN 13: 9780792331926
• Binding: Hardcover
• Condition: Good
• Weight: 800 grams
• Seller catalogs:
  • Social Sciences

About this title

Synopsis

Quantitative Sociodynamics presents a general strategy for interdisciplinary model building and its application to a quantitative description of behavioural changes based on social interaction processes. Originally, the crucial methods for the modeling of complex systems (stochastic methods and nonlinear dynamics) were developed in physics but they have very often proved their explanatory power in chemistry, biology, economics and the social sciences.
Quantitative Sociodynamics provides a unified and comprehensive overview of the different stochastic methods, their interrelations and properties. In addition, it introduces the most important concepts from nonlinear dynamics (synergetics, chaos theory). The applicability of these fascinating concepts to social phenomena is carefully discussed. By incorporating decision-theoretical approaches a very fundamental dynamic model is obtained which seems to open new perspectives in the social sciences. It includes many established models as special cases, e.g. the logistic equation, the gravity model, some diffusion models, the evolutionary game theory and the social field theory, but it also implies numerous new results. Examples concerning opinion formation, migration, social field theory; the self-organization of behavioural conventions as well as the behaviour of customers and voters are presented and illustrated by computer simulations.
Quantitative Sociodynamics is relevant both for social scientists and natural scientists who are interested in the application of stochastic and synergetics concepts to interdisciplinary topics.

From the Back Cover

This new edition of Quantitative Sociodynamics presents a general strategy for interdisciplinary model building and its application to a quantitative description of behavioral changes based on social interaction processes. Originally, the crucial methods for the modeling of complex systems (stochastic methods and nonlinear dynamics) were developed in physics and mathematics, but they have very often proven their explanatory power in chemistry, biology, economics and the social sciences as well. Quantitative Sociodynamics provides a unified and comprehensive overview of the different stochastic methods, their interrelations and properties. In addition, it introduces important concepts from nonlinear dynamics (e.g. synergetics, chaos theory). The applicability of these fascinating concepts to social phenomena is carefully discussed. By incorporating decision-theoretical approaches, a fundamental dynamic model is obtained, which opens new perspectives in the social sciences. It includes many established models as special cases, e.g. the logistic equation, the gravity model, some diffusion models, evolutionary game theory and social field theory. Moreover, it implies numerous new results and is relevant for various application areas, such as opinion formation, migration, the self-organization of behavioral conventions, and the behavior of customers and voters. Theoretical results are complemented and illustrated by numerous computer simulations.

Quantitative Sociodynamics is relevant both for social scientists and natural scientists who are interested in the application of stochastic and synergetics concepts to interdisciplinary topics.