| Computational Modeling Contributor(s): Taber, Charles S. (Author), Timpone, Richard John (Author) |
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ISBN: 0803972709 ISBN-13: 9780803972704 Publisher: Sage Publications, Inc OUR PRICE: $39.90 Product Type: Paperback - Other Formats Published: March 1996 Annotation: 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. |
| Additional Information |
| BISAC Categories: - Computers | Computer Simulation - Social Science | Research |
| Dewey: 003.3 |
| LCCN: 95050246 |
| Series: Quantitative Applications in the Social Sciences |
| Physical Information: 0.26" H x 5.4" W x 8.42" (0.29 lbs) 104 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: Computational modelling allows researchers to combine the rich detail of qualitative research with the rigour of quantitative and formal research, as well as to represent complex structures and processes within a theoretical model. After an introduction to modelling, the authors discuss the role of computational methods in the social sciences. They treat computational methods, including dynamic simulation, knowledge-based models and machine learning, as a single broad 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. |
Contributor Bio(s): Taber, Charles S.: - Professor of the department of political science |