Previous: Two Step Rationality Up: Issues in Knowledge Level Modelling Next: The Nature of Problem Solving
Newell proposed to model in terms of knowledge, goals and actions. That is all of structure that there is at the knowledge level. The various approaches toward Knowledge Level modelling use different but related notions. Task, generic task, problem solving method, inference, domain model, case model, role-limiting method and knowledge role are only some of the terms one encounters in the literature. The reader is referred to some of the other chapters in this volume for detailed explanations on these.
Three terms - or at least the concepts they indicate - seem to gain wide acceptance in the knowledge systems community: domain model, task model and problem solving method. They represent three different perspectives on the knowledge level and correspond to three paradigmatic approaches to KL-modelling (Fig. ):
Model oriented approaches in knowledge engineering are quite old  and reasoning from first principles has become an active line of research. Here the idea is that the kind of knowledge that is available about a domain gives a clue for the kind of reasoning that is being done for a certain task. Terms such as 'causal' or 'qualitative' refer to the kinds of domain models that are being used. Such a domain model provides a reasoner with a repertoire of reasoning steps that are not specific for a task but can be usefully combined for a variety of tasks, like for prediction and diagnosis. Domain and model ontologies are studied for example in OntoLingua  and in CommonKADS . It is becoming increasingly clear that domain knowledge is an important indicator for the kind of KL-model that is appropriate .
The original KADS methodology is prototypical of the task oriented approach . An application task (or real-life task) is decomposed into a series of so called generic tasks. A generic task is basically no more than an index to an interpretation model, an inference structure for the generic task. Such an interpretation model is independent of domain knowledge. It only requires certain inferences to be possible in the domain but does not say what models these have to be based on. So KADS advocates an analysis of the task, prior to making decisions on domain knowledge. The early work on Generic Tasks  was also task oriented.
The research by John McDermott and his team at Digital  is prototypical for the method oriented approach. They have embarked on an encompassing effort to catalogue problem solving methods and to systematically probe for their scope of applicability by doing a series of applications and variations on them. The idea that the notion of problem solving method makes sense independent of the notion of task was convincingly argued for by Clancey  but in practice methods seem to remain closely linked to tasks. The Generic Tasks of Chandrasekaran  are closer to methods than they are to tasks. For example, CSRL embodies a classification method that can be used for other tasks than diagnosis alone (compare  and ). Method instantiation and configuration is also an important element in the work on Protege  and Protege-II .
The domain, task and method perspective are related views on problem solving. Each of them describes knowledge in its own language: model specific, task specific, method specific. A KL-model brings together these three perspectives in a coherent model. More and more the importance of all three aspects is being recognized and taken into account . These KL-models, however, focus on describing the process of problem solving and have little to say about what problem solving is. For example a role-limiting method makes explicit control over actions that, when it is followed leads to the completion of some goal. However, the aim of a genuine knowledge level theory of problem solving must focus on 'why' questions. Why is an action taken? A knowledge level answer to this should refer to the world, rather than to a control regime imposed by a method. This leads us to considering more seriously what problem solving is all about.