Laps: Cases to Models to Complete Expert Systems

In the short history of expert systems, a variety of approaches have been used to tackle the difficult problem of knowledge acquisition, among which are the following common types: consulting a library of models; using automatic induction from cases; and using triadic differentiation, which is repeated contrasting of two of the expected output of an expert system with a third. To be topical, all this knowledge-acquisition research has been done in the name of constructing expert systems in an easier, faster, and more maintainable manner because there is a growing consensus that expert systems are stuck on a productivity plateau in light of first-generation tools still being used without an effective knowledge-acquisition and knowledge-structuring front end. Contrary to many prevailing approaches to knowledge acquisition, Laps, our expert-interviewing software, begins by soliciting cases from the expert, but it does not end there. Its uniqueness lies in the fact that it interweaves knowledge gathering, organizing, and testing. Laps begins with a case in the form of a sample solution path elicited from the domain expert.