Abstract
The term ‘knowledge engineering’ was coined in the 1980s to reference the processes whereby knowledge was elicited from human experts in order to develop knowledge-based systems. It was seen as reflecting an alternative paradigm for system engineering in which, for systems which were difficult to analyze in themselves but were subject to human activities, one modeled the human operators' skills rather than the system itself. In the 1980s, expert systems development appeared radically different from conventional systems development, but in the 1990s it is time to re-evaluate the reality and significance of the differences. The growth of expert systems development coincided with that of high-performance workstations, improvements in the efficiency of symbolic programming languages, and the development of graphic user interfaces. Much of what has been attributed to ‘expert systems’ may be seen as a halo effect of these other technologies. More fundamentally, the knowledge acquisition community has moved from an ‘expertise transfer’ to a ‘knowledge modeling’ perspective, in which knowledge is seen as not so much transferred from the expert as built in conjunction with the expert as a means of emulating his or her skill. This paper develops a modeling framework for systems engineering that encompasses systems modeling, task modeling, and knowledge modeling, and allows knowledge engineering and software engineering to be seen as part of a unified developmental process. This framework is used to evaluate what novel contributions the ‘knowledge engineering’ paradigm has made, and how these impact software engineering.
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References
Akkermans, H., Harmelen, F.v., Shreiber, G. and Wielinga, B. (1992). “A formalisation of knowledge-level models for knowledge acquisition.” International Journal of Intelligent Systems: to appear.
Boose, J.H. and Bradshaw, J.M. (1987). “Expertise transfer and complex problems: using AQUINAS as a knowledge acquisition workbench for knowledge-based systems.” International Journal of Man-Machine Studies 26: 3–28.
Clancey, W.J. (1989). “Viewing knowledge bases as qualitative models.” IEEE Expert 4(2): 9–23.
Compton, P. and Jansen, R. (1990). “A philosophical basis for knowledge acquisition.” Knowledge Acquisition 2(3): 241–258.
Dreyfus, H.L. and Dreyfus, S.E. (1986). Mind over Machine: The Power of Human Intuition and Expertise in the Era of the Computer. New York, Free Press.
Feigenbaum, E., McCorduck, P. and Nii, H.P. (1988). The Rise of the Expert Company. New York, Times Books.
Gaines, B.R. and Shaw, M.L.G. (1985). “From fuzzy sets to expert systems.” Fuzzy Sets and Systems 36(1–2): 5–16.
Gaines, B.R. and Shaw, M.L.G. (1992). “Basing knowledge acquisition tools in personal construct psychology.” Knowledge Engineering Review: to appear.
Gaines, B.R., Shaw, M.L.G. and Woodward, J.B. (1992). “Modeling as a framework for knowledge acquisition methodologies and tools.” International Journal of Intelligent Systems: to appear.
Gentner, D. and Stevens, A., Ed. (1983). Mental Models. Hillsdale, New Jersey, Erlbaum.
Gomez, F. and Segami, C. (1990). “Knowledge acquisition from natural language for expert systems based on classification problem-solving methods.” Knowledge Acquisition 2(2): 107–128.
Li, X. (1991). “What's so bad about rule-based programming?” IEEE Software: 103–105.
Michalski, R.S. and Chilausky, R.L. (1980). “Knowledge acquisition by encoding expert rules versus computer induction from examples—A case study involving soyabean pathology.” International Journal of Man-Machine Studies 12: 63–87.
Norman, D.A. (1983). Some observations on mental models. Mental Models. Hillsdale, New Jersey, Erlbaum. 7–14.
Shaw, M.L.G. (1980). On Becoming A Personal Scientist: Interactive Computer Elicitation of Personal Models Of The World. London, Academic Press.
Shaw, M.L.G. and Gaines, B.R. (1987). “KITTEN: Knowledge initiation & transfer tools for experts and novices.” International Journal of Man-Machine Studies 27(3): 251–280.
Shaw, M.L.G. and Gaines, B.R. (1989). “A methodology for recognizing conflict, correspondence, consensus and contrast in a knowledge acquisition system.” Knowledge Acquisition 1(4): 341–363.
Sternberg, R.J. and Caruso, D.R. (1985). Practical modes of knowing. Learning and Teaching the Ways of Knowing. Chicago, Illinois, University of Chicago Press. 133–158.
Woodward, B. (1990). “Knowledge engineering at the front-end: defining the domain.” Knowledge Acquisition 2(1): 73–94.
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© 1992 Springer-Verlag Berlin Heidelberg
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Shaw, M.L.G., Gaines, B.R. (1992). The synthesis of knowledge engineering and software engineering. In: Loucopoulos, P. (eds) Advanced Information Systems Engineering. CAiSE 1992. Lecture Notes in Computer Science, vol 593. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0035133
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DOI: https://doi.org/10.1007/BFb0035133
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