The Algorithmic Nature of Problem Solving

  • F. J. Garlick
  • G. L. Leonard


The work on this paper arose from some studies into how practitioners solved the problem of knowledge elicitation. These studies were illuminating since the most common situation seemed to be that no strategy was employed and that the activity in essence was based on chance. in other words when practitioners were asked what strategy they were using the most common answer was that they did not know but they could do it anyway.


Soft System Methodology Repertory Grid Good Problem Knowledge Elicitation Common Answer 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    D. Harel, “Algorithmes — the Spirit of Computing”, Addison-Wesley, London, (1987).Google Scholar
  2. 2.
    D. Knuth, “Fundamental Algorithms”, 2ed, Addison-Wesley, Wokingham, (1979).Google Scholar
  3. 3.
    G. Gibbs, “Improving Student Learning”, the Oxford Centre for Staff Development, Oxford, (1990).Google Scholar
  4. 4.
    R.A. Rodrigues-Ulloa, the Problem Solving System: Another Problem Content System, Systems Practice, 1(3), 243–257 (1988).CrossRefGoogle Scholar
  5. 5.
    A. Hart, “Knowledge Acquisition for Expert Systems”, Kogan Page, London, (1989).Google Scholar
  6. 6.
    A.J. Kelly, “A Theory of Personality”, the Norton Library, New York, (1963). the Open University, “Complexity, Management and Change”, T301 Block IV, Open University Press (1983).Google Scholar
  7. 7.
    P.B. Checkland and J. Scholes, “Soft Systems Methodology in Action”, Wiley, Chichester, (1991)Google Scholar
  8. 8.
    D. Chapman, Planning for Conjunctive Goals, Artificial Intelligence, 32: 333–377, (1987).CrossRefGoogle Scholar
  9. 9.
    E. De Bono, “The Mechanism of Mind”, Simon & Schuster, New York, (1969).Google Scholar
  10. 10.
    B. Schneiderman, “Designing the User Interface”, Addison-Wesley, New York, (1987).Google Scholar
  11. 11.
    R.J. Brachman and H.J. Levesque, ed., “Readings in Knowledge Representation”, Morgan Kaufmann, New York, (1985).Google Scholar
  12. 12.
    M.J. Stific and D.G. Bobrow, Object-Oriented Programming — Themes and Variations, The AI Magazine, 2(4), 40–62, (1984).Google Scholar
  13. 13.
    P. Johnson, “Human Computer Interaction”, McGraw-Hill, Maidenhead, (1992).Google Scholar

Copyright information

© Springer Science+Business Media New York 1993

Authors and Affiliations

  • F. J. Garlick
    • 1
  • G. L. Leonard
    • 1
  1. 1.Department of Information ScienceThe University of PortsmouthPortsmouthGreat Britain

Personalised recommendations