Issues in the verification of knowledge in rule-based systems

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As expert system technology spreads, the need for verification of system knowledge assumes greater importance. This paper addresses the issues involved in demonstrating a rule-based system to be free from error. A holistic perspective is adopted, wherein sorces, manifestations, and effects of errors are identified. A general taxonomy is created, and the implications for system performance and development outlined. Existing strategies for knowledge verification are surveyed, their applicability assessed, and some directions for systematic verification suggested.

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