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RESEARCH ARTICLE   Open Access    

Principles and practice in verifying rule-based systems*

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  • Abstract: This paper surveys the verification of expert system knowledge bases by detecting anomalies. Such anomalies are highly indicative of errors in the knowledge base. The paper is in two parts. The first part describes four types of anomaly: redundancy, ambivalence, circularity, and deficiency. We consider rule bases which are based on first-order logic, and explain the anomalies in terms of the syntax and semantics of logic. The second part presents a review of five programs which have been built to detect various subsets of the anomalies. The four anomalies provide a framework for comparing the capabilities of the five tools, and we highlight the strengths and weaknesses of each approach. This paper therefore provides not only a set of underlying principles for performing knowledge base verification through anomaly detection, but also a survey of the state-of-the-art in building practical tools for carrying out such verification. The reader of this paper is expected to be familiar with first-order logic.
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  • Cite this article

    Alun D. Preece, Rajjan Shinghal, Aïda Batarekh. 1992. Principles and practice in verifying rule-based systems*. The Knowledge Engineering Review. 7: doi: 10.1017/S026988890000624X
    Alun D. Preece, Rajjan Shinghal, Aïda Batarekh. 1992. Principles and practice in verifying rule-based systems*. The Knowledge Engineering Review. 7: doi: 10.1017/S026988890000624X

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RESEARCH ARTICLE   Open Access    

Principles and practice in verifying rule-based systems*

The Knowledge Engineering Review  7 Article number: 10.1017/S026988890000624X  (1992)  |  Cite this article

Abstract: Abstract: This paper surveys the verification of expert system knowledge bases by detecting anomalies. Such anomalies are highly indicative of errors in the knowledge base. The paper is in two parts. The first part describes four types of anomaly: redundancy, ambivalence, circularity, and deficiency. We consider rule bases which are based on first-order logic, and explain the anomalies in terms of the syntax and semantics of logic. The second part presents a review of five programs which have been built to detect various subsets of the anomalies. The four anomalies provide a framework for comparing the capabilities of the five tools, and we highlight the strengths and weaknesses of each approach. This paper therefore provides not only a set of underlying principles for performing knowledge base verification through anomaly detection, but also a survey of the state-of-the-art in building practical tools for carrying out such verification. The reader of this paper is expected to be familiar with first-order logic.

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    Alun D. Preece, Rajjan Shinghal, Aïda Batarekh. 1992. Principles and practice in verifying rule-based systems*. The Knowledge Engineering Review. 7: doi: 10.1017/S026988890000624X
    Alun D. Preece, Rajjan Shinghal, Aïda Batarekh. 1992. Principles and practice in verifying rule-based systems*. The Knowledge Engineering Review. 7: doi: 10.1017/S026988890000624X
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