Computational Modeling

1. Auflage 1996
ISBN: 978-0-8039-7270-4
Verlag: Sage Publications

Buch, Englisch, Band 113, 104 Seiten, Format (B × H): 140 mm x 216 mm, Gewicht: 143 g

Reihe: Quantitative Applications in the Social Sciences

Why model computationally? Because these methods allow researchers to combine the rich detail of qualitative research with the rigor of quantitative and formal research, as well as to represent complex structures and processes within a theoretical model. The authors treat computational methods, including dynamic simulation (Monte Carlo methods), knowledge-based models (semantic networks, frame systems, and rule-based systems), and machine learning (connectionism, rule induction, and genetic algorithms), as a single broad-based class of research tools and develop a framework for incorporating them within established traditions of social science research. They provide a concise description of each method and a variety of social science illustrations including four detailed examples. Common to most of these methods is a straightforward underlying approach: simulate the theory by running the program. Computational Modeling concludes with a discussion of ways to validate computational models.

Autoren/Hrsg.

Taber, Charles S.

Timpone, Richard J.

Timpone, Richard John

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Kybernetik, Systemtheorie, Komplexe Systeme
• Mathematik | Informatik Mathematik Mathematik Interdisziplinär Systemtheorie
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Demographie, Demoskopie
• Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computersimulation & Modelle, 3-D Graphik

Inhaltsverzeichnis

Introduction
Dynamic Simulation Models
Knowledge-Based Systems
Models of Machine Learning
Evaluating Computational Models

Über Autor(innen)

Taber, Charles S.
Professor of the department of political science