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Expert System Applications pp 1–77Cite as

Representing Control Knowledge as Abstract Tasks and Metarules

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Part of the book series: Symbolic Computation ((1064))

Abstract

A poorly designed knowledge base can be as cryptic as an arbitrary program and just as difficult to maintain. Representing inference procedures abstractly, separately from domain facts and relations, makes the design more transparent and explainable. The combination of abstract procedures and a relational language for organizing domain knowledge provides a generic framework for constructing knowledge bases for related problems in other domains and also provides a useful starting point for studying the nature of strategies. In HERACLES inference procedures are represented as abstract metarules, expressed in a form of the predicate calculus, organized and controlled as rule sets. A compiler converts the rules into Lisp code and allows domain relations to be encoded as arbitrary data structures for efficiency. Examples are given of the explanation and teaching capabilities afforded by this representation. Different perspectives for understanding HERACLES’ inference procedure and how it defines a relational knowledge base are discussed in some detail.

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Author information

Authors and Affiliations

  1. Stanford Knowledge Systems Laboratory, 701 Welch Road, Building C, Palo Alto, CA, 94304, USA

    William J. Clancey & Conrad Bock

Authors
  1. William J. Clancey
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  2. Conrad Bock
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Editors and Affiliations

  1. Institute of Computer Science, Polish Academy of Sciences, PKiN, pok. 1050, Warsaw, Poland

    Leonard Bolc

  2. Computing Research Laboratory, New Mexico State University, P.O. Box 30001, Las Cruces, NM, 88003, USA

    Michael J. Coombs

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© 1988 Springer-Verlag Berlin Heidelberg

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Clancey, W.J., Bock, C. (1988). Representing Control Knowledge as Abstract Tasks and Metarules. In: Bolc, L., Coombs, M.J. (eds) Expert System Applications. Symbolic Computation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83314-4_1

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  • DOI: https://doi.org/10.1007/978-3-642-83314-4_1

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  • Print ISBN: 978-3-642-83316-8

  • Online ISBN: 978-3-642-83314-4

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