Expert systems / Robert A. Benfer, Edward E. Brent, Jr., Louanna Furbee.
This book introduces the process of expert systems development as a model for acquiring, representing and validating knowledge about relatively limited domains. Many examples derive from the authors' own development experiences in the social sciences, both with normative and with descriptive mo...
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| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Ebook |
| Language: | English |
| Published: |
Newbury Park, Calif. :
Sage Publications,
[1991]
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| Series: | Quantitative applications in the social sciences ;
no. 07-077. |
| Subjects: | |
| Online Access: | SAGE |
Table of Contents:
- 1. Artificial intelligence and expert systems
- Introduction: What are expert systems?
- Kinds of knowledge
- Expert system development environments
- Architecture of expert systems
- Strengths and weaknesses of expert systems
- Representing and reasoning about knowledge
- 2. Applications of expert systems in the social sciences
- Applications of expert systems to theorizing
- Modeling: Use of an AI program as the theory itself
- Simulating actual historical events (simulating a theory with an expert system)
- Expert systems for designing and conducting research
- Expert systems and data collection
- Data analysis
- Cognitive modeling
- Teaching
- Applying and disseminating knowledge
- 3. Knowledge acquisition
- The ethnoscience approach
- Knowledge acquisition methods
- Applications-classification
- Applications-taking action
- 4. Pragmatic strategies
- Strategies for summarizing and editing the knowledge base
- Reducing the complexity of the knowledge base
- Selecting a method of handling uncertainty
- Deciding to use an inductive or deductive approach
- Choosing representation and inference strategies
- The expert system development process
- 5. Multiple experts and testing the models
- Knowledge that adheres among multiple experts
- Testing the model
- Validity
- How expert systems can improve social science.