Concept formation using ITERATE building rule models for efficient reasoning
Gautam Biswas, Gyesung Lee, Jerry B. Weinberg · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
This paper discusses the application of a conceptual clustering algorithm called ITERATE to improve complex problem solving. More specifically, we apply the ITERATE system to build a hierarchy of rule models from sets of rules defined for PLAYMAKER, an expert system for characterizing hydrocarbon fields and plays in terms of their essential geological characteristics for the purposes of prospect analysis. PLAYMAKER is built on MIDST, an expert system shell that employs task-specific reasoning structures. The rule model hierarchy derived by ITERATE is then used with the task-specific reasoning structures to develop a more efficient and focused reasoning mechanism. A set of case studies were conducted to demonstrate the improved performance of the reasoning system.