Computational modeling
By: Charles S. Taber, Richard J. Timpone.
Contributors: Timpone, Richard J.
Series: Sage university papers series.; no. 07-113
Publisher: Sage Publications
Published: 1996
Place of publication: Thousand Oaks, Calif
Language: eng
Number of pages: 95
Subjects: Social sciences -- Mathematical models.; Social sciences -- Data processing.
Description: In this introduction to computational modelling the authors provide a concise description of computational methods including dynamic simulation, knowledge-based models and machine learning, as a single broad class of research tools.
Notes: Includes bibliographical references (p. 89-93).
Table of contents: title: Introduction: Beyond platforms and on-ramps. Models and computational models. Why model computationally? Where is computational modeling likely to be most useful? Drawbacks of computational modeling. General stages in a computational modeling project. An overview  of the following chapters; title: Dynamic simulation models: Dynamic simulation. Cellular automata; title: Knowledge-based systems: Semantic networks. Frame systems. Rule-based expert systems. Hybrid systems.; title: Models of machine learning: Connectionist models. ID3. Genetic algorithms; title: Evaluating computational models: Truth. Beauty. Justice. Conclusion.