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Personal construct psychology foundations for knowledge acquisition and representation

Life Cycle and Methodologies Methodologies
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

Knowledge Acquisition Semantic Network Personal Construct Visual Language Repertory Grid 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    R.H. Abraham and C.D. Shaw, Dynamics: The Geometry of Behavior, Santa Cruz, California: Aerial Press. 1984.Google Scholar
  2. [2]
    J.R. Adams-Webber, Personal Construct Theory: Concepts and Applications, Chichester, UK: Wiley. 1979.Google Scholar
  3. [3]
    J.M. Anglin, Word, Object, and Conceptual Development, New York: Norton. 1977.Google Scholar
  4. [4]
    J.H. Boose, “Personal construct theory and the transfer of human expertise,” in Proceedings AAAI-84. American Association for Artificial Intelligence: California. p. 27–33, 1984.Google Scholar
  5. [5]
    J.H. Boose, Expertise Transfer for Expert Systems, Amsterdam: Elsevier. 1986.Google Scholar
  6. [6]
    J.H. Boose and J.M. Bradshaw, “Expertise transfer and complex problems: using AQUINAS as a knowledge acquisition workbench for knowledge-based systems,” International Journal of Man-Machine Studies, vol. 26, pp. 3–28, 1987.Google Scholar
  7. [7]
    A. Borgida, R.J. Brachman, D.L. McGuiness, and L.A. Resnick, “CLASSIC: a structural data model for objects,” in Proceedings of 1989 SIGMOD Conference on the Management of Data. ACM Press: New York. p. 58–67, 1989.Google Scholar
  8. [8]
    R.J. Brachman, “What's in a concept: structural foundations for semantic nets,” International Journal of Man-Machine Studies, vol. 9, pp. 127–152, 1977.Google Scholar
  9. [9]
    R.J. Brachman, “What IS-A is and isn't,” IEEE Computer, vol. 16, no. 10 pp. 30–36, 1983.Google Scholar
  10. [10]
    R.J. Brachman and J. Schmolze, “An overview of the KL-ONE knowledge representation system,” Cognitive Science, vol. 9, no. 2 pp. 171–216, 1985.Google Scholar
  11. [11]
    J.M. Bradshaw, J.H. Boose, S.P. Covington, and P.J. Russo, “How to do with grids what people say you can't,” in Proceedings of the Third AAAI Knowledge Acquisition for Knowledge-Based Systems Workshop, J.H. Boose and B.R. Gaines, Editor. University of Calgary: Banff. p. 3–1–3–15, 1988.Google Scholar
  12. [12]
    G.P. Copeland and S.N. Khoshafian, Identity and versions for complex objects. MCC Technical Report DB-138-86, Austin, Texas: MCC. 1986.Google Scholar
  13. [13]
    J. Diederich, I. Ruhmann, and M. May, “KRITON: A knowledge acquisition tool for expert systems,” International Journal of Man-Machine Studies, vol. 26, no. 1 pp. 29–40, 1987.Google Scholar
  14. [14]
    E. Domany, J.L. Hemmen, and K. Schulten, ed. Models of Neural Networks. Springer: Berlin. 1991.Google Scholar
  15. [15]
    L. Eshelman, D. Ehret, J. McDermott, and M. Tan, “MOLE: A tenacious knowledge acquisition tool,” International Journal of Man-Machine Studies, vol. 26, no. 1 pp. 41–54, 1987.Google Scholar
  16. [16]
    Euclid, The Elements, New York: Dover Publications. 1908.Google Scholar
  17. [17]
    K.M. Ford, A. Cañas, J. Jones, H. Stahl, J. Novak, and J. Adams-Webber, “ICONKAT: an integrated constructivist knowledge acquisition tool,” Knowledge Acquisition, vol. 3, no. 2 pp. 215–236, 1990.Google Scholar
  18. [18]
    F. Fransella and D. Bannister, ed. A Manual for Repertory Grid Technique. Academic Press: London. 1977.Google Scholar
  19. [19]
    G. Frege, “On sense and reference,” in Translations from the Philosophical Writings of Gottlieb Frege, P. Geach and M. Black, Editor. Basil Blackwell: Oxford. p. 56–78., 1970.Google Scholar
  20. [20]
    B.R. Gaines, “An ounce of knowledge is worth a ton of data: quantitative studies of the trade-off between expertise and data based on statistically well-founded empirical induction,” in Proceedings of the Sixth International Workshop on Machine Learning. Morgan Kaufmann: San Mateo, California. p. 156–159, 1989.Google Scholar
  21. [21]
    B.R. Gaines, “Empirical investigations of knowledge representation servers: Design issues and applications experience with KRS,” ACM SIGART Bulletin, vol. 2, no. 3 pp. 45–56, 1991.Google Scholar
  22. [22]
    B.R. Gaines, “An interactive visual language for term subsumption visual languages,” in IJCAI'91: Proceedings of the Twelfth International Joint Conference on Artificial Intelligence. Morgan Kaufmann: San Mateo, California. p. 817–823, 1991.Google Scholar
  23. [23]
    B.R. Gaines and M.L.G. Shaw, “New directions in the analysis and interactive elicitation of personal construct systems,” International Journal Man-Machine Studies, vol. 13, pp. 81–116, 1980.Google Scholar
  24. [24]
    B.R. Gaines and M.L.G. Shaw, “A programme for the development of a systems methodology of knowledge and action,” in General Systems Research and Design: Precursors and Futures, W.J. Reckmeyer, Editor. Society for General Systems Research: Louisville, Kentucky. p. 255–264, 1981.Google Scholar
  25. [25]
    B.R. Gaines and M.L.G. Shaw, “Hierarchies of distinctions as generators of system theories,” in Proceedings of the Society for General Systems Research International Conference, A.W. Smith, Editor. Society for General Systems Research: Louisville, Kentucky. p. 559–566, 1984.Google Scholar
  26. [26]
    B.R. Gaines and M.L.G. Shaw, “Induction of inference rules for expert systems,” Fuzzy Sets and Systems, vol. 18, no. 3 pp. 315–328, 1986.Google Scholar
  27. [27]
    B.R. Gaines and M.L.G. Shaw, “Cognitive and logical foundations of knowledge acquisition,” in Proceedings of the Fifth AAAI Knowledge Acquisition for Knowledge-Based Systems Workshop, J.H.&.G. Boose B.R., Editor. University of Calgary: Banff, Canada. p. 9–1–9–24, 1990.Google Scholar
  28. [28]
    B.R. Gaines and M.L.G. Shaw, “Integrated knowledge acquisition architectures,” Journal for Intelligent Information Systems, vol. 1, no. 1 pp. 9–34, 1992.Google Scholar
  29. [29]
    B.R. Gaines and M.L.G. Shaw, “Basing knowledge acquisition tools in personal construct psychology,” Knowledge Engineering Review, vol. 8, no. 1 pp. to appear, 1993.Google Scholar
  30. [30]
    C. Garg-Janardan and G. Salvendy, “A conceptual framework for knowledge elicitation,” International Journal of Man-Machine Studies, vol. 26, no. 4 pp. 521–531, 1987.Google Scholar
  31. [31]
    J.J.E. Gracia, “Individuals as instances,” Reviews of Metaphysics, vol. 37, no. 1 pp. 37–59, 1983.Google Scholar
  32. [32]
    W.S. Hatcher, The Logical Foundations of Mathematics, Oxford: Pergamon Press. 1982.Google Scholar
  33. [33]
    J.R. Hindley and J.P. Seldon, Introduction to Combinators and lamda-calculus, Cambridge, UK: Cambridge University Press. 1986.Google Scholar
  34. [34]
    D.N. Hinkle, The change of personal constructs from the viewpoint of a theory of implications. Ohio State University. 1965.Google Scholar
  35. [35]
    J. Hintikka, Knowledge and Belief, Ithaca, New York: Cornell University Press. 1962.Google Scholar
  36. [36]
    J. Hintikka, “The modes of modality,” Acta Philosophica Fennica, vol. 16, pp. 65–81, 1963.Google Scholar
  37. [37]
    W.P. Jones, “Bringing corporate knowledge into focus with CAMEO,” Knowledge Acquisition, vol. 2, no. 3 pp. 207–239, 1990.Google Scholar
  38. [38]
    G.A. Kelly, The Psychology of Personal Constructs, New York: Norton. 1955.Google Scholar
  39. [39]
    G.A. Kelly, “Aldous: the personable computer,” in Computer Simulation of Personality, S.S. Tomkins and S. Messick, Editor. Wiley: New York. p. 221–229, 1963.Google Scholar
  40. [40]
    G.A. Kelly, “A mathematical approach to psychology,” in Clinical Psychology and Personality: The Selected Papers of George Kelly, B. Maher, Editor. Wiley: New York. p. 94–113, 1969.Google Scholar
  41. [41]
    G.A. Kelly, “A brief introduction to personal construct theory,” in Perspectives in Personal Construct Theory, D. Bannister, Editor. Academic Press: London. p. 1–29, 1970.Google Scholar
  42. [42]
    G. Klinker, J. Bentolila, S. Genetet, M. Grimes, and J. McDermott, “KNACK— report-driven knowledge acquisition,” International Journal of Man-Machine Studies, vol. 26, no. 1 pp. 65–79, 1987.Google Scholar
  43. [43]
    D.R. Lachterman, The Ethics of Geometry, New York: Routledge. 1989.Google Scholar
  44. [44]
    E.J. Lemmon, C.A. Meredith, D. Meredith, A.N. Prior, and I. Thomas, “Calculi of pure strict implication,” in Philosophical Logic, J.W. Davis, D.J. Hockney, andW.K. Wilson, Editor. Reidel: Dordrecht, Holland. p. 215–250, 1969.Google Scholar
  45. [45]
    G.E.R. Lloyd, Polarity and Analogy, Cambridge, UK: Cambridge University Press. 1966.Google Scholar
  46. [46]
    S. Mac Lane, Categories for the Working Mathematician, New York: Springer-Verlag. 1971.Google Scholar
  47. [47]
    B. Maher, ed. Clinical Psychology and Personality: The Selected Papers of George Kelly. Wiley: New York. 1969.Google Scholar
  48. [48]
    J.C. Mancuso and J.R. Adams-Webber, ed. The Construing Person. Praeger: New York. 1982.Google Scholar
  49. [49]
    J.C. Mancuso and M.L.G. Shaw, ed. Cognition and Personal structure: Computer Access and Analysis. Praeger: New York. 1988.Google Scholar
  50. [50]
    R.B. Marcus, “Interpreting quantification,” Inquiry, vol. 5, pp. 252–259, 1962.Google Scholar
  51. [51]
    S. Marcus, “Taking backtracking with a grain of SALT,” International Journal of Man-Machine Studies, vol. 26, no. 4 pp. 393–398, 1987.Google Scholar
  52. [52]
    D. Maybury-Lewis and U. Almagor, ed. The Attraction of Opposites. University of Michigan Press: Ann Arbor. 1989.Google Scholar
  53. [53]
    A. Meinong, On Assumptions, Berkely: University of California Press. 1983.Google Scholar
  54. [54]
    J.N. Mohanty, Husserl and Frege, Bloomington, Indiana: Indiana University Press. 1982.Google Scholar
  55. [55]
    E. Motta, M. Eisenstadt, K. Pitman, and M. West, “Support for knowledge acquisition in the knowledge engineer's assistant (KEATS),” Expert Systems, vol. 5, no. 1 pp. 6–28, 1988.Google Scholar
  56. [56]
    B. Russell, “On denoting,” Mind, vol. 14, pp. 479–493, 1905.Google Scholar
  57. [57]
    B. Russell, History of Western Philosophy, London: Allen & Unwin. 1946.Google Scholar
  58. [58]
    S.C. Shapiro, “The SNePS semantic network processing system,” in Associative Networks: Representation and Use of Knowledge by Computers, N.V. Findler, Editor. Academic Press: New York. p. 179–203, 1979.Google Scholar
  59. [59]
    M.L.G. Shaw, “Conversational heuristics for enhancing personal understanding of the world,” in General Systems Research: A Science, A Methodology, A Technology, B.R. Gaines, Editor. Society for General Systems Research: Louisville, Kentucky. p. 270–277, 1979.Google Scholar
  60. [60]
    M.L.G. Shaw, On Becoming A Personal Scientist: Interactive Computer Elicitation of Personal Models Of The World, London: Academic Press. 1980.Google Scholar
  61. [61]
    M.L.G. Shaw, ed. Recent Advances in Personal Construct Technology. Academic Press: London. 1981.Google Scholar
  62. [62]
    M.L.G. Shaw and B.R. Gaines, “A computer aid to knowledge engineering,” in Proceedings of British Computer Society Conference on Expert Systems. British Computer Society: Cambridge. p. 263–271, 1983.Google Scholar
  63. [63]
    M.L.G. Shaw and B.R. Gaines, “KITTEN: Knowledge initiation and transfer tools for experts and novices,” International Journal of Man-Machine Studies, vol. 27, no. 3 pp. 251–280, 1987.Google Scholar
  64. [64]
    L.S. Vygotsky, Thought and Language, Cambridge, Massachusetts: MIT Press. 1934.Google Scholar
  65. [65]
    J.V. Wertsch, ed. Culture, Communication and Cognition: Vygotskian Perspectives. Cambridge University Press: Cambridge, UK. 1985.Google Scholar
  66. [66]
    J. Woods, The Logic of Fiction, The Hague: Mouton. 1974.Google Scholar
  67. [67]
    W.A. Woods, “What's in a link: Foundations for semantic networks,” in Representation and Understanding: Studies in Cognitive Science, D.G. Bobrow and A.M. Collins, Editor. Academic Press: New York. p. 35–82, 1975.Google Scholar
  68. [68]
    B. Woodward, “Knowledge engineering at the front-end: defining the domain,” Knowledge Acquisition, vol. 2, no. 1 pp. 73–94, 1990.Google Scholar
  69. [69]
    L.A. Zadeh, “The concept of state in system theory,” in Views on General Systems Theory: Proceedings of the Second Systems Symposium at Case Institute of Technology, M.D. Mesarovic, Editor. John Wiley: New York. 1964.Google Scholar
  70. [70]
    E.N. Zalta, Abstract Objects, Dordrecht:, Holland: Reidel. 1983.Google Scholar
  71. [71]
    E.N. Zalta, Intensional Logic and the Metaphysics of Intentionality, Cambridge, Massachusetts: MIT Press. 1988.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  1. 1.Knowledge Science InstituteUniversity of CalgaryCalgaryCanada

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