KNOWLEDGE MODELING DIRECTED BY SITUATION-SPECIFIC MODELS

Clancey (1992) proposed the model-construction framework as a way to e xplain the reasoning of knowledge-based systems (KBSs), based on his r ealization that all KBSs construct implicit or explicit situation-spec ific models (SSMs). An SSM is a rational argument that explains the so lution produced for a specific problem situation pertaining to a targe t application task (e.g. SSMs constructed for typical diagnosis tasks are causal arguments having the structure of a proof). From a knowledg e engineering perspective it makes sense that the notion of an SSM sho uld play a major role in the modeling of tasks. Motivated by this view , we present a structured knowledge modeling methodology called SSM-di rected knowledge modeling (SSM-DKM). In SSM-DKM, an SSM is a central s tructure that drives the entire modeling endeavor. In light of this fa ct, we explain how SSM-DKM supports three main stages in the knowledge engineering process-conceptualization, formalization and validation a nd instantiation-and illustrate the application of SSM-DKM to a medica l diagnosis task. The knowledge model that SSM-DKM produces for a targ et application task has two appealing traits. First, the model embodie s explicit knowledge about the ontology of SSMs that the task entails creating as solutions, thus enabling the construction of a KBS that ma kes these SSMs explicit. Second, the model captures strategic (or prob lem-solving) knowledge in declarative terms pertaining to the ontology of SSMs created for the task. Both these beneficial traits have been illustrated in the context of ACE-SSM, a KBS architecture that constru cts explicit SSMs (Benaroch, 1998). (C) 1998 Academic Press.