Article ID: | iaor19901170 |
Country: | United Kingdom |
Volume: | 41 |
Issue: | 5 |
Start Page Number: | 447 |
End Page Number: | 458 |
Publication Date: | May 1990 |
Journal: | Journal of the Operational Research Society |
Authors: | Neale I.M. |
Keywords: | artificial intelligence |
The benefits of a qualitative modelling approach to building knowledge-based systems include better project control, communication between participants, more accurate validation and easier maintenance. Knowledge acquisition from experts will be more successful if a conceptual model is developed from a knowledge level description, to act as a publicly examinable basis for system design. Analytical tools are available to structure both content and process knowledge on paper, before any commitment is made to implementation. The role of abstraction in developing models of generic tasks as a set of templates for conceptual model development is reviewed, with particular regard to knowledge acquisition tools. Modelling problem-solving methods, especially for constructive tasks such as planning, is more difficult than modelling content knowledge. Epistemological support for conceptual abstraction, particularly at middle levels, remains adequate.