Concluding remarks

In this paper I have tried to detail a number of key issues that confront die knowledge engineering enterprise. I have concentrated, in particular, on die problems inherent in providing computational support for die K A process. I have explored these in die context of our own experience in building acquisition workbenches.

There is a large and difficult research agenda ahead of us. Nevertheless, in a number of areas wc can sec the emergence of ideas that will, I believe, assume a central role in the future. These include: die deployment of model based acquisition methods, reuse of knowledge structures

within and between application domains, and the development of knowledgeable knowledge acquisition tools.

Finally, we should not forget that the formative influences on knowledge acquisition have been eclectic and interdisciplinary. In the attempt to secure a sound basis for knowledge engineering we must retain this broad based view of our subject.

Section 10 References

1. Anjewierden, A . , Wielemaker, J. & Toussaint, C. (1990) Shelley — Computer Aided Knowledge Engineering. In B . Wielinga, J. Boose, B. Gaines, G . Schreiber & M . van Someren, (ed), Current Trends in Knowledge Acquisition, pages 313-338. Amsterdam: IOS Press.

2. Boose, J.H., Shema, D.B and Bradsi, J.M. (1989) Recent progress in AQUINAS: a knowledge acquisition workbench, Knowledge Acquisition, volume 1(2), Academic Press, London.

3. Breuker. J. &. Wielinga, B. (1987) Use of models in die interpretation of verbal data.

In AJL. Kidd, (ed), Knowledge Acquisition for Expert Systems, a practical handbook, New York: Plenum Press.

4. Breuker. J. &. Wielinga, B. (1989) Model driven knowledge acquisition. In P. Guida and G. Tasso, (eds), Topics in the design of expert systems, Amsterdam:. North Holland.

5. Burton, A . , Shadbolt, N . , Hedgecock, A . & Rugg, G. (1987) A formal evaluation of knowledge elicitation techniques for expert systems. In D Moralee, (ed), Research and development in expert systems, IV, 136-145.

6. Burton, A . , Shadbolt, N . , Rugg, G. & Hedgecock, A . (1988) Knowledge elicitation techniques in classification domains. ECAI-88, 85-90

7. Bylander, T. & Chandrasekaran, B. (1988) Generic tasks in knowledge-based reasoning:

The 'right' level of abstraction for knowledge acquisition. In B . Gaines and J.Boose, (eds), Knowledge Acquisition for Knowledge Based Systems, volume 1, pages 65-77. Academic Press, London, 1988.

8. Chase, W.G. & Simon, H.A. (1973) Perception in Chess Cognitive Psychology, 4, 55-81 9. Chi, M . , Claser, R. and Farr, M . (Eds) (1988) The Nature of Expertise. New Jersey: L E A . 10. Clancey, W. (1985) Heuristic classification. Artificial Intelligence, 27:289-350.

11. Clark, P. & Niblett, T. (1989) The CN2 induction algorithm. Machine Learning Journal, 3(4), pages 261-283.

12. Cleaves, D. A . (1987) Cognitive biases and corrective techniques: Proposals for improvin-gelicitation procedures for knowledge-based systems. International Journal of Man-Machine Studies, 27,155-166.

13. Eshelman, L . (1989) M O L E : A knowledge-acquisition tool for cover-and-differentiate sys-tems. In S. Marcus, (ed), Automating Knowledge Acquisition for Expert Systems, pages 37-80. Dordrecht: Kluwer Academic Publishers.

14. Gaines, B. R. & Shaw, M . L . G . (1986) Induction of inference rules for expert systems.

Fuzzy Sets and Systems, 8 (3), 315-328.

15. Ginsberg, M . L . (1991) Knowledge Interchange Format: The K I F of Death. A l Magazine, 12(3), pp. 57-63.

16. Hart, A . (1986) Knowledge Acquisition for Expert Systems. London: Kogan Page.

17. Hink, R. F. and Woods, D. L . (1987) How humans process uncertain knowledge. A l Magazine, 8, 41-53.

18. Hoffman, R. R. (1987) The Problem of Extracting the Knowledge of Experts from die Perspective of Experimental Psychology. A l Magazine, 8, pp. 53-66.

19. Johnson-Laird, P. N . (1983) Mental models. Cambridge. Cambridge University Press.

20. Kahn, G„ Nowlan, S. & McDermott, J. (1986) Strategies for Knowledge Acquisition. PAMI Special Issue on Knowledge Representation.

21. Kahncman, D., Slovic, P. and Tversky, A . (Eds) (1982) Judgement under uncertainty:

Heuristics and biases. New York: Cambridge University Press.

22. Karbach, W., Linstcr, M . & Voss, A . (1990) Model-Based Approaches : one label —one idea? In B . Wielinga, J. Boose, B. Gaines, G. Schreiber & M . van Someren, (ed), Current Trends in Knowledge Acquisition, pages 313-338. Amsterdam: IOS Press.

23. Kidd, A . L . (Ed.) (1987) Knowledge Acquisition for Expert Systems: A Practical Handbook.

New York: Plenum Press.

24. Kindle, K . W., Cann, R. S., Craig, M . R. and Martin, T. J. (1989) PFPS: Personal Financial Planning System. In H . Schorr and A . Rappaport, (eds), Innovative Applications of Artificial Intelligence MIT Press: Cambridge, Mass.

25. Lesgold, A . , Rubinson, H . , Feltovich, P., Glascr, R., Klopfer, D. and Wang, Y . (1988) Expertise in a complex skill: diagnosing X-ray pictures. In Chi, M.T.H., Glaser, R. & Farr, M.J. (eds) The Nature of Expertise Lawrence Erlbaum; London.

26. McAllcster, D. (1980) A n oudook on truth maintenance. Technical report, MIT A l L A B . 27. Major, N . & Reichgelt, H . (1990) Alto: A n automated laddering tool. In B. Wiclinga,

J. Boose, B. Gaines, G. Schreiber & M . van Someren, (ed),Current Trends in Knowledge Acquisition, pages 222-236. Amsterdam: IOS Press.

28. Marcus, S. (1988) Automatic knowledge acquisition for expert systems. New York: Kluwer.

29. Meyer, M . A . , Booker, J. M . and Bradshaw, J. M . (1990) A flexible six-step program for defining and handling bias in knowledge elicitation. In B. Wielinga, J. Boose, B. Gaines, G. Schreiber, M . van Someren, (eds), Current trends in knowledge acquisition. Amsterdam:

IOS Press.

30. Meyer, M and Booker, J. (1991) Eliciting and analysing expert judgement: a proactical guide. Knowledge Based Systems Vol 5, Academic Press, London.

31. Michalski, R.S. (1969) On die quasi-minimal solution of hte general covering problem.

Proceedings of the 5th International Symposium on Information Processing (FCIP 69), Vol.

A3 (Switching Circuits), Bled, Yugoslavia, pages 125-128.

32. Motta, E., Rajan, T., Domingue, J. & Eisenstadt, M . (1990) Methodological foundations of KEATS, die knowledge engineer's assistant. In B. Wielinga, J. Boose, B . Gaines, G.

Schreiber & M . van Someren, (cd),Currcnt Trends in Knowledge Acquisition, pages 257-275. Amsterdam: IOS Press.

33. Musen, M . A., Fagin, L . M . , Combs, D.M. & Shortliffc, E.H. (1987) Use of a domain model to drive an interactive knowledge-editing tool. International Journal of Man-Machine Studies, 26, pages 105-121.

34. Ncchcs, R., Fikcs, R., Finin, T., Gruber, T., Paul, R., Senator, T. and Swartout, W. (1991) Enabling Technology for Knowledge Sharing. A l Magazine, 12(3), pp. 36-56.

35. Reichgelt, H., Major, N . & Jackson, P. (1990) Commonsloop: The manual. Technical report, A l Group, Dcpt Psychology, University of Nottingham.

36. Reichgelt, H . and Shadbolt, N.R. (1991a). Knowledgeable knowledge acquisition. In L . Steels and B. Smith, Eds. AISB91 Springer-Verlag

37. Rcichgclt, H . and Shadbolt, N.R. (1991b). ProtoKEW: A knowledge-based system for knowledge acquisition. In D, Slceman and N . Bemscn, Eds. Research directions in cognitive science volume 5: Artificial Intelligence. Lawrence Erlbaum.

38. Rips, L. J. and Marcus, S. L . (1977) Supposition and the analysis of conditional sentences.

In Just, M . A . and Carpenter, P. A . (eds), Cognitive processes in comprehension. Hillsdale, NJ: Erlbaum.

39. Rugg, G & Shadboll, N . (1991) On die limitations of the repertory grid technique. Technical report, A l Group, Dept Psychology, University of Nottingham.

40. Shadbolt, N . & Burton, M . (1989) The empirical study of knowledge elicitation techniques.

SIG ART Newsletter, 108, April 1989, A C M Press.

41. Shadbolt, N . & Burton, M . (1990) Knowledge elicitation. In J. Wilson and N . Corlett, (eds), Evaluation of Human Work: A Practical Ergonomics Methodology, pages 321-346. Taylor and Francis.

42. Shadbolt, N . & Wielinga, B. (1990) Knowledge based knowledge acquisition: die next generation of support tools. In B. Wiclinga, J. Boose, B. Gaines, G. Schreiber & M . van Someren, (ed), Current Trends in Knowledge Acquisition, pages 313-338. Amsterdam: IOS Press.

43. Slaucr, P. E. (1987) Building expert systems: cognitive emulation. Chichester: Ellis Horwood.

44. Steels, L. (1990) Components of expertise. The Al Magazine, 11: 30-62.

45. Wason, P. C. (1961) Response to affirmative and negative binary statements. British Journal of Psychology, 52 ,273-81.

46. Welbank, M . A . (1983) A Review of Knowledge Acquisition Techniques for Expert Systems.

British Telecom Research, Martlcsham Heath.

47. Yorkc, D.M. (1978) Repertory grids in educational research: some methodological consid-erations. British Journal of Social and Clinical Psychology, 9, 108-21.