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Representation of control knowledge in expert systems

Janice S. Aikins

Open publisher page 19 citations

Abstract

This paper presents the results of research done on the representation of control knowledge in rule-based expert systems. ’ It discusses the problems of representing co&o1 knowledge implicitly in object-level inference rules and presents specific examples from a MYCIN-like consultation system called PUFF. As an alternative, the explicit representation of conerol knowledge in sloes of a frame-like data structure is demonstrated in the CENTAUR system. Explicit representation of control knowledge has significant advantages both for the acquisition and modification of domain knowledge and for explanations of how knowledge is used in the expert system.

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What this paper is about

This paper presents the results of research done on the representation of control knowledge in rule-based expert systems. ’ It discusses the problems of representing co&o1 knowledge implicitly in object-level inference rules and presents specific examples from a MYCIN-like consultation system called PUFF. As an alternative, the explicit representation of conerol knowledge in sloes of a frame-like data structure is demonstrated in the CENTAUR system. Explicit representation of control knowledge has significant advantages both for the acquisition and modification of domain knowledge and for explanations of how knowledge is used in the expert system.

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OpenAlex reports 19 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper presents the results of research done on the representation of control knowledge in rule-based expert systems. ’ It discusses the problems of representing co&o1 knowledge implicitly in object-level inference rules and presents specific examples from a MYCIN-like consultation system called PUFF. As an alternative, the explicit representation of conerol knowledge in sloes of a frame-like data structure is demonstrated in the CENTAUR system. Explicit representation of control knowledge has significant advantages both for the acquisition and modification of domain knowledge and for explanations of how knowledge is used in the expert system.

Key concepts: Knowledge representation and reasoning, Computer science, Expert system, Domain knowledge, Knowledge-based systems, Legal expert system, Representation (politics), Inference

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