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Personal construct psychology foundations for knowledge acquisition and representation

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Book cover Knowledge Acquisition for Knowledge-Based Systems (EKAW 1993)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 723))

Abstract

Personal construct psychology is a theory of individual and group psychological and social processes that has been used extensively in knowledge acquisition research to model the cognitive processes of human experts. The psychology has the advantage of taking a constructivist position appropriate to the modeling of specialist human knowledge but basing this on a positivist scientific position that characterizes human conceptual structures in axiomatic terms that translate directly to computational form. The repertory grid knowledge elicitation methodology is directly derived from personal construct psychology. In its original form, this methodology was based on the notion of dichotomous constructs and did not encompass the ordinal relations between them captured in semantic net elicitation. However, it was extended in successive tools developed for applied knowledge acquisition and tested in a wide variety of applications. This paper gives an overview of personal construct psychology and its expression as an intensional logic describing the cognitive processes of anticipatory agents as a basis for a comprehensive theory of knowledge acquisition and representation.

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Authors and Affiliations

  1. Knowledge Science Institute, University of Calgary, T2N 1N4, Calgary, Alberta, Canada

    Mildred L. G. Shaw & Brian R. Gaines

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  1. Mildred L. G. Shaw
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  2. Brian R. Gaines
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N. Aussenac G. Boy B. Gaines M. Linster J. -G. Ganascia Y. Kodratoff

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© 1993 Springer-Verlag Berlin Heidelberg

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Shaw, M.L.G., Gaines, B.R. (1993). Personal construct psychology foundations for knowledge acquisition and representation. In: Aussenac, N., Boy, G., Gaines, B., Linster, M., Ganascia, J.G., Kodratoff, Y. (eds) Knowledge Acquisition for Knowledge-Based Systems. EKAW 1993. Lecture Notes in Computer Science, vol 723. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57253-8_58

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  • DOI: https://doi.org/10.1007/3-540-57253-8_58

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  • Online ISBN: 978-3-540-47996-3

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