A pictorial aid for programming expert systems

Abstract

The knowledge engineering and software development tasks involved in constructing software for an expert system are very different from the task of designing an imperative program. Some of the problems in the construction of a rule-based expert system include deducing the heuristics of the expert, converting these heuristics into a working taxonomy and rule base, and ordering the rule base so that the system performs efficiently and correctly. A pictorial method of knowledge representation that we call a "k-tree" greatly facilitates these tasks.

References

1. fr1 Schwartz, E. "A Pictorial Method of Knowledge Representation" pp. 425-426 Proceedings of The Fourth Conference on Artificial Intelligence Applications, Computer Society Press of the IEEE, 1988.
2. fr2 Schwartz, E. "Manhattanville College Expert Academic Advisor-Prliminary Report" pp. 38-41, Sigart Newsletter, Number 103, January 1988.
3. fr3 Kiernan, G., Koltun, A., Psihountas, G., Schwartz, E., "Some Techniques for Minimizing and Optimizing the Rule Base of An Expert System" pp. 218-222, Proceedings Focus on Software 1988 ACM Computer Scince Conference, Association for Computing Machinery, 1988.

Index Terms

• Computing methodologies

  • Artificial intelligence