KNOWLEDGE REPRESENTATION IN EXPERT SYSTEMS
Date
1985-08-01
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Abstract
Knowledge representation is frequently said to be the central issue in
expert systems research. The definition and special characteristics of
an expert system demand that three criteria for knowledge representation
be met: expressive adequacy, the ability to represent the necessary
distinctions of the domain in the representation; explicitness, the
accessibility of all necessary naturalness, the case with which the
representation captures the structure and content of knowledge in the
domain. To date, most expert systems have relied on one of two
knowledge representation formalisms, rule-based production systems or
frame-based conceptual graphs. A survey of the theoretical literature
shows that both these formalisms are considered appropriate
representations to meet the three criteria. An examination of systems
utilizing these formalisms indicates that this is not the case. Important
discrepancies exist between these theoretical arguments and the existing
successful expert systems. In order to investigate these issues further
an expert system for the interpretation of personality inventories in
clinical psychology was designed and two prototypes were implemented.
Based on the examination of the literature and the discussion of the
prototypes the definitions of the three criteria appearing in the
literature are seen to be inadequate. More precise definitions, taking
into account the field of expert systems and other areas of research
into knowledge representation, are proposed and issues crucial to the
evaluation of any representation are raised.
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Computer Science