Knowledge Representation and Conversion for Hybrid Expert Systems
Author:
Chambers T. L.1, Parkinson A. R.2
Affiliation:
1. Department of Mechanical Engineering, University of Southwestern Louisiana, Lafayette, Louisiana 2. Department of Mechanical Engineering, Brigham Young University, Provo, Utah
Abstract
Many different knowledge representations, such as rules and frames, have been proposed for use with engineering expert systems. Every knowledge representation has certain inherent strengths and weaknesses. A knowledge engineer can exploit the advantages, and avoid the pitfalls, of different common knowledge representations if the knowledge can be mapped from one representation to another as needed. This paper derives the mappings between rules, logic diagrams, decision tables and decision trees using the calculus of truth-functional logic. The mappings for frames have also been derived by Chambers and Parkinson (1995). The logical mappings between these representations are illustrated through a simple example, the limitations of the technique are discussed, and the utility of the technique for the rapid-prototyping and validation of engineering expert systems is introduced. The technique is then applied to three engineering applications, showing great improvements in the resulting knowledge base.
Publisher
ASME International
Subject
Computer Graphics and Computer-Aided Design,Computer Science Applications,Mechanical Engineering,Mechanics of Materials
Reference37 articles.
1. Carter, K., C., 1977, A Contemporary Introduction to Logic with Applications, MacMillan Book Co., New York, NY. 2. Chambers, T. L., 1994, “Multiple Knowledge Representations for the Rapid Prototyping and Validation of Engineering Expert Systems,” Ph.D. Dissertation, Brigham Young University, Provo, UT. 3. Chambers, T. L., Parkinson, A. R., 1995, “Knowledge Representation and Conversion for Hybrid Expert Systems,” Proceedings of the 1995 Design Engineering Technical Conference, Vol. 1, Advances in Design Automation, 1995, presented at the 21st Annual Design Automation Conference, Sept. 17–20, 1995, Boston, MA, pp. 9–16. 4. Cragun B. J. , SteudelH. J., 1987, “A Decision-Table-Based Processor for Checking Completeness and Consistency in Rule-Based Expert Systems,” Int. J. Man-Machine Studies, Vol. 26, No. 6, pp. 633–648. 5. Crookston, R. K., “Expert System Spring Design,” Masters Thesis, Brigham Young University, Provo, UT.
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