Generalized directive models: integrating model development and knowledge acquisition

doi:10.1006/ijhc.1998.0216

International Journal of Human-Computer Studies

Volume 49, Issue 4, October 1998, Pages 497-522

https://doi.org/10.1006/ijhc.1998.0216 Get rights and content

Abstract

The Generalized directive model (GDM) methodology for knowledge acquisition is introduced. For GDMs to work two assumptions are required: that knowledge acquisition has a cyclic structure interleaving episodes of model development and domain KA, and that increased specification of one part of a model does not affect other parts. The use of GDMs is illustrated with a real-world example from an Airborne Early Warning system, showing the development of a model for one sub-task using the PC-based GDM tool from the commercial workbench PC-PACK. There is also a small example of a GDM analysis extending an already existing model. Finally, GDMs are compared with the decompositional CommonKADS library.

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Regular ArticleGeneralized directive models: integrating model development and knowledge acquisition

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Regular Article
Generalized directive models: integrating model development and knowledge acquisition