| Abstract: | Model-based reasoning (MBR) is a means of reasoning about models of all kinds, as appropriate to the task at hand. This includes adaptation of models in response to changes in a problem-solving context or task goals. Thus, MBR exemplifies the characteristics of a smart adaptive system. Constructing appropriate models and matching them to the best inference engines requires a means of describing or defining models. This can be achieved by means of a set of generic model properties. As well as defining models one may decompose the problem domain into a number of tasks to be performed. It then becomes possible to design appropriate models for the domain by mapping these tasks to the model properties. This mapping can be instantiated procedurally, however more generality will result if a model-based approach is taken. As a step towards that goal quality function deployment is investigated as a suitable design method. |
