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Computational modeling [electronic resource] / Charles S. Taber, Richard J. Timpone.

By: Taber, Charles S.
Contributor(s): Timpone, Richard J.
Material type: TextTextSeries: Quantitative applications in the social sciences: no. 07-113.Publisher: Thousand Oaks, Calif. : Sage Publications, c1996Description: 1 online resource (viii, 95 p.) : ill.ISBN: 0585216800 (electronic bk.); 9780585216805 (electronic bk.); 9781412983716 (electronic bk.); 1412983711 (electronic bk.).Subject(s): Social sciences -- Mathematical models | Social sciences -- Data processing | COMPUTERS -- Computer Simulation | Sciences sociales -- Mod�eles math�ematiques | Sciences sociales -- Informatique | Computermodellen | Sociale wetenschappen | Sozialwissenschaften | Computersimulation | Simulations Use of ComputersGenre/Form: Electronic books.Additional physical formats: Print version:: Computational modeling.DDC classification: 003/.3 Other classification: 70.03 Online resources: EBSCOhost
Contents:
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 -- Dynamic simulation models: Dynamic simulation. Cellular automata -- Knowledge-based systems: Semantic networks. Frame systems. Rule-based expert systems. Hybrid systems. -- Models of machine learning: Connectionist models. ID3.
Summary: 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.
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Includes bibliographical references (p. 89-93).

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 -- Dynamic simulation models: Dynamic simulation. Cellular automata -- Knowledge-based systems: Semantic networks. Frame systems. Rule-based expert systems. Hybrid systems. -- Models of machine learning: Connectionist models. ID3.

Description based on print version record.

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.

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Other editions of this work

Computational modeling by Taber, Charles S. ©1996
Computational modeling by Taber, Charles S. ©1996
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