AKARS-1 : an Automatic Knowledge Acquisition and Refinement System

M. L. WONG, K. S. LEUNG

Research output: Book Chapters | Papers in Conference ProceedingsBook Chapter

Abstract

Expert Systems are definitely one of the major success of Artificial Intelligence. Unfortunately, the knowledge acquisition bottleneck hampers the development of Expert Systems in practical domains. Machine Learning is a promising solution to this problem and this paper discusses an Automatic Knowledge Acquisition and Refinement System(AKARS-1) for knowledge in rule form. Two major components AKARS-1, the learning component (AKA-1) and the Heuristic Refinement System (HERES) are detailed. A prototype of AKA-1 has been implemented and three case studies are used to validate this prototype. A comparison between ID3 and AKA-1 is presented. HERES employs heuristics and statistical methods to guide its search for refinements. These methods are also discussed in the paper.
Original languageEnglish
Title of host publicationKnowledge acquisition for knowledge-based systems
EditorsH. Motoda, R. Mizoguchi, J. Boose, B. Gaines
PublisherIOS Press
Pages161-174
Number of pages14
ISBN (Print)9789051990447
Publication statusPublished - 1991
Externally publishedYes

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    WONG, M. L., & LEUNG, K. S. (1991). AKARS-1 : an Automatic Knowledge Acquisition and Refinement System. In H. Motoda, R. Mizoguchi, J. Boose, & B. Gaines (Eds.), Knowledge acquisition for knowledge-based systems (pp. 161-174). IOS Press.