Abstract
Making inferences and decisions in an imprecise and changing world limits the potential leverage of a system, particularly, in occurrence of exceptions. Many rule-based systems which make inferences using rules attempt to deal with expected exceptions by augmenting the rules in the knowledge base. The result is a whole tree of rules which widens the search space of a goal. This paper introduces several kinds of exceptions and presents a methodology for representing exceptions at the object level and meta level of rule-based systems. The proposed approach accommodates instance exceptions as well as assertion exceptions, hence allowing for the recognition of exception rules as distinct from the normal rules in rule-based systems.
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© 1990 Springer-Verlag Berlin Heidelberg
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Tan, P.L., Dillon, T.S., Zeleznikow, J. (1990). Representing exceptions in rule-based systems. In: Barter, C.J., Brooks, M.J. (eds) AI '88. AI 1988. Lecture Notes in Computer Science, vol 406. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-52062-7_83
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DOI: https://doi.org/10.1007/3-540-52062-7_83
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