Automatic knowledge acquisition for expert systems

It is suggested that if an expert system truly lives up to its name and given some basic, observable information on a domain´s structure and characteristics, the system should be able to perform its inferences to a high degree of confidence and, most important, learn from its inferences to refine them as it works more and more in the domain. An approach to automatic knowledge acquisition that attempts to achieve such a goal is presented. In order to focus on the philosophy and methods needed to realize this goal, a subset of expert systems was chosen. Fault isolation expert systems for electronic and/or electromechanical systems were selected for the development of this acquisition process. Target systems to be fault isolated are typically constructed of readily separable components known as the lowest replaceable units (LRUs), which are interconnected, receive a finite set of external inputs and offer a finite set of outputs. The application in industry of a user-friendly knowledge acquisition tool for use by nonexperts is definitely needed, and its cost savings could be significant