The epistemology of a rule-based expert system —a framework for explanation

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Abstract

Production rules are a popular representation for encoding heuristic knowledge in programs for scientific and medical problem solving. However, experience with one of these programs, mycin, indicates that the representation has serious limitations: people other than the original rule authors find it difficult to modify the rule set, and the rules are unsuitable for use in other settings, such as for application to teaching. These problems are rooted in fundamental limitations in mycin's original rule representation: the view that expert knowledge can be encoded as a uniform, weakly structured set of if/then associations is found to be wanting.

To illustrate these problems, this paper examines mycin's rules from the perspective of a teacher trying to justify them and to convey a problem-solving approach. We discover that individual rules play different roles, have different kinds of justifications, and are constructed using different rationales for the ordering and choice of premise clauses. This design knowledge, consisting of structural and strategic concepts which lie outside the representation, is shown to be procedurally embedded in the rules. Moreover, because the data/hypothesis associations are themselves a proceduralized form of underlying disease models, they can only be supported by appealing to this deeper level of knowledge. Making explicit this structural, strategic and support knowledge enhances the ability to understand and modify the system.

References (34)

  • R.J. Brachman

    What's in a concept: structural foundations for semantic networks

    BBN Report No. 3433

    (1976)
  • J.S. Brown et al.

    Artificial intelligence and learning strategies

  • B.G. Buchanan et al.

    heuristic dendral: a program for generating explanatory hypotheses in organic chemistry

  • B.G. Buchanan et al.

    Rediscovering some problems of artificial intelligence in the context of organic chemistry

  • W.J. Clancey

    Transfer of rule-based expertise through a tutorial dialogue

  • W.J. Clancey et al.

    Intelligent computer-aided instruction for medical diagnosis

  • W.J. Clancey et al.

    neomycin: Reconfiguring a rule-based expert system for application to teaching

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