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On making expert systems more like experts
Author(s) -
SWARTOUT WILLIAM R.,
SMOLIAR STEPHEN W.
Publication year - 1987
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/j.1468-0394.1987.tb00143.x
Subject(s) - computer science , expert system , subject matter expert , legal expert system , domain (mathematical analysis) , terminology , domain knowledge , model based reasoning , knowledge management , artificial intelligence , data science , management science , knowledge representation and reasoning , mathematics , economics , mathematical analysis , linguistics , philosophy
Expert systems still lack the skill of an expert when it comes to providing explanations of the results of expert reasoning. This is because while such systems may implement knowledge which is sufficient to mimic the performance of an expert, they do not necessarily model the expertise upon which that performance is based. Such a model must include knowledge of that domain's terminology, knowledge of domain facts, and knowledge of problem‐solving methods. The Explainable Expert Systems project has been exploring a new paradigm for expert system development that is intended to capture such missing knowledge and make it available for explanation. This paper will discuss the principles behind this paradigm and consider two systems that employ it.