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KA Process Support Through Generalised Directive Models

  • Conference paper
Second Generation Expert Systems

Abstract

In this paper we describe Generalised Directive Models and their instantiation in the ACKnowledge Knowledge Engineering Workbench. We have developed a context sensitive rewrite grammar that allows us to capture a large class of inference layer models. We use the grammar to progressively refine the model of problem solving for an application. It is also used as the basis of the scheduling of KA activities and the selection of KA tools.

This paper is partially a reprint of [25] but with an extended knowledge acquisition scenario (Sect. 4)

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Author information

Authors and Affiliations

  1. Social Science Informatics, Department of Psychology, University of Amsterdam, Roeterstraat 15, 1018 WB, Amsterdam, The Netherlands

    Peter Terpstra, Gertjan van Heijst & Bob Wielinga

  2. AI Group, Department of Psychology, Nottingham University, University Park, Nottingham, NG7 2RD, UK

    Nigel Shadbolt

Authors
  1. Peter Terpstra
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  2. Gertjan van Heijst
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  3. Nigel Shadbolt
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  4. Bob Wielinga
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Editor information

Editors and Affiliations

  1. Service Systèmes Experts, Renault, 860 Quai Stalingrad, 92109, Boulogne-Billancourt, France

    Jean-Marc David

  2. Direction des Etudes et Recherches, Electricité de France, 1, Av. du Général de Gaulle, 92141, Clamart Cedex, France

    Jean-Paul Krivine

  3. School of Computer Science, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213-3890, USA

    Reid Simmons

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© 1993 Springer-Verlag Berlin Heidelberg

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Terpstra, P., van Heijst, G., Shadbolt, N., Wielinga, B. (1993). KA Process Support Through Generalised Directive Models. In: David, JM., Krivine, JP., Simmons, R. (eds) Second Generation Expert Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77927-5_19

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  • DOI: https://doi.org/10.1007/978-3-642-77927-5_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-77929-9

  • Online ISBN: 978-3-642-77927-5

  • eBook Packages: Springer Book Archive

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