Buchtitel: Proceedings of 10th European Workshop on Knowledge Acquisition, Modeling, and Management (EKAW`97)
Reihe: Lecture Notes in Artificial Intelligence (LNAI)
In recent years two main technologies for knowledge sharing and reuse have emerged: ontologies and problem solving methods (PSMs). Ontologies specify reusable conceptualizations which can be shared by multiple reasoning components communicating during a problem solving process. PSMs describe in a domain-independent way the generic reasoning steps and knowledge types needed to perform a task. Typically PSMs are specified in a task-specific fashion, using modelling frameworks which describe their control and inference structures as well as their knowledge requirements and competence. In this paper we discuss a novel approach to PSM specification, which is based on the use of formal ontologies. In particular our specifications abstract from control, data flow and other dynamic aspects of PSMs to focus on the logical theory associated with a PSM (method ontology). This approach concentrates on the competence and knowledge requirements of a PSM, rather than internal control details, thus enabling black-box-style reuse. In the paper we also look at the nature of PSM specifications and we show that these can be characterised in a task-independent style as generic search strategies. The resulting "modelling gap" between method-independent task specifications and task-independent method ontologies can be bridged by constructing the relevant adapter ontology, which reformulates the method ontology in task-specific terms. An important aspect of the ontology-centred approach described here is that, in contrast with other characterisations of task-independent PSMs, it does away with the simple, binary distinction between weak and strong methods. We argue that any method can be defined in either task-independent or task-dependent style and therefore such distinction is of limited utility in PSM reuse. The differences between PSMs which affect reuse concern the ontological commitments which they make with respect to domain knowledge and goal specifications.