A GENERALIZED INTELLIGENT PROBLEM SOLVING SYSTEM BASED ON A RELATIONAL MODEL FOR KNOWLEDGE REPRESENTATION (SUPPORT SYSTEMS, EXPERT, DECISION AIDS).

Abstract

Over the past decade, two types of decision aids, i.e., decision support systems (DSS) and expert systems (ES), have been developed along parallel paths, showing some significant differences in their software architectures, capabilities, limitations, and other characteristics. The synergy of DSS and ES, however, has great potential for helping make possible a generalized approach to developing a decision aid that is powerful, intelligent, and friendly. This research establishes a framework for such decision aids in order to determine the elementary components and their interactions. Based on this framework, a generalized intelligent problem solving system (GIPSS) is deveolped as a decision aid generator. A relational model is designed to provide a unified logical view of each type of knowledge including factual data, modeling knowledge, and heuristic rules. In this knowledge model, a currently existing relational DBMS, with some extension, is utilized to manage each type of knowledge. For this purpose a relational resolution inference mechanism has been devised. A prototype GIPSS has been developed based on this framework. Two domain specific decision aids, COCOMO which estimates software development effort and cost, and CAPO which finds optimal process organization, have been implemented by using the GIPSS as a decision aid generator, demonstrating such features as its dynamic modeling capabilities and learning capabilities.