Using Fuzzy logic for automating knowledge acquisition

Knowledge acquisition is a key phase in construction of expert systems. This process is very much dependent on the nature of the domain knowledge. In particular, knowledge acquisition is a tedious task when modeling domains with tacit knowledge. Despite fuzzy logic has been used for knowledge acquisition in such domains, a large portion of the process is manually operated. This paper presents an approach to automated knowledge acquisition using fuzzy logic for the domains with tacit knowledge. The novel approach allows the user or developer to directly interact with the system and enter tacit form of knowledge Acquisition of tacit knowledge is supported through questionnaire emulating the role of an interview of domain expert by the knowledge engineer. Tacit knowledge acquired through this session will be analyzed by statistical technique of principle component analysis to reveal the available dependencies in the knowledge acquired. The principle components generated will be transferred to fuzzy logic module for automatic construction of the fuzzy membership functions. Further, in a usual manner, system can acquired fuzzy rules relevant to manipulation of domain knowledge. Thus, collectively, the approach is consisted of principles component analyzer, fuzzy logic module and a fuzzy expert system. The approach has been developed to be able to connect with a standard expert system shell. Currently, it has been integrated with FLEX expert system shell. The development has been done using Visual basic and the system runs on Windows platform. The approach has been applied to many domains include Ayurvedic domain of classification of individuals. It has shown 78%. accuracy in using the tacit knowledge for reasoning in the relevant domain. Performances were very close to handling tacit knowledge by the human expert in tacit domain.