Date of Award

Spring 1991

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Science

Committee Director

Stewart N. T. Shen

Committee Member

S. V. Rao

Committee Member

Larry Wilson

Committee Member

Christian Wild

Abstract

Knowledge base systems (expert systems) are entering a critical stage as interest spreads from university research to practical applications. If knowledge base systems are to withstand this transition, special attention must be paid to checking their effectiveness. The issue of effectiveness analysis of knowledge base systems has been largely ignored and few works have been published in this field. This dissertation shows how the effectiveness of a knowledge base system can be defined, discussed and analyzed at the knowledge base system level and the knowledge base level. We characterize the effectiveness of a knowledge base system in terms of minimality, termination, completeness and consistency. In order to resolve these issues, we propose a general framework for checking these properties. This framework includes models KBS and KB for knowledge base systems and knowledge bases, respectively. These models provide an environment in which we can discuss and analyze the effectiveness of a knowledge base system. This framework leads to analysis for rule set properties and a set of problem formulations for each of the following: minimality, termination, completeness and consistency. In this dissertation, we have designed a set of algorithms for resolving these problems and given some computational results.

DOI

10.25777/ahdc-cf32

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