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1993 Volume 8
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RESEARCH ARTICLE   Open Access    

Knowledge acquisition tools based on personal construct psychology

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  • Abstract: Knowledge acquisition research supports the generation of knowledge-based systems through the development of principles, techniques, methodologies and tools. What differentiates knowledge-based system development from conventional system development is the emphasis on in-depth understanding and formalization of the relations between the conceptual structures underlying expert performance and the computational structures capable of emulating that performance.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 takes a constructivist position appropriate to the modelling of human knowledge processes, but develops this through the characterization of human conceptual structures in axiomatic terms that translate directly to computational form. In particular, there is a close correspondence between the intensional logics of knowledge, belief and action developed in personal construct psychology, and the intensional logics for formal knowledge representation developed in artificial intelligence research as term subsumption, or KL-ONE-like, systems.This paper gives an overview of personal construct psychology and its expression as an intensional logic describing the cognitive processes of anticipatory agents, and uses this to survey knowledge acquisition tools deriving from personal construct psychology.
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  • Cite this article

    Brian R. Gaines, Mildred L. G. Shaw. 1993. Knowledge acquisition tools based on personal construct psychology. The Knowledge Engineering Review. 8: doi: 10.1017/S0269888900000060
    Brian R. Gaines, Mildred L. G. Shaw. 1993. Knowledge acquisition tools based on personal construct psychology. The Knowledge Engineering Review. 8: doi: 10.1017/S0269888900000060
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RESEARCH ARTICLE   Open Access    

Knowledge acquisition tools based on personal construct psychology

  • Published online: 07 July 2009
The Knowledge Engineering Review  8,  Article number: 10.1017/S0269888900000060  (1993)  |  Cite this article

Abstract: Abstract: Knowledge acquisition research supports the generation of knowledge-based systems through the development of principles, techniques, methodologies and tools. What differentiates knowledge-based system development from conventional system development is the emphasis on in-depth understanding and formalization of the relations between the conceptual structures underlying expert performance and the computational structures capable of emulating that performance.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 takes a constructivist position appropriate to the modelling of human knowledge processes, but develops this through the characterization of human conceptual structures in axiomatic terms that translate directly to computational form. In particular, there is a close correspondence between the intensional logics of knowledge, belief and action developed in personal construct psychology, and the intensional logics for formal knowledge representation developed in artificial intelligence research as term subsumption, or KL-ONE-like, systems.This paper gives an overview of personal construct psychology and its expression as an intensional logic describing the cognitive processes of anticipatory agents, and uses this to survey knowledge acquisition tools deriving from personal construct psychology.

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    Brian R. Gaines, Mildred L. G. Shaw. 1993. Knowledge acquisition tools based on personal construct psychology. The Knowledge Engineering Review. 8: doi: 10.1017/S0269888900000060
    Brian R. Gaines, Mildred L. G. Shaw. 1993. Knowledge acquisition tools based on personal construct psychology. The Knowledge Engineering Review. 8: doi: 10.1017/S0269888900000060
    shu

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