Significant Distinctions Only: Context-dependent Automated Qualitative Modeling
Peter Struss''Z, Martin Sachenbacher · 2003
Qualitative modeling means making the essential distinctions only . Compositional modeling requires to state behavior models of system constituents (e.g components) independently of their context. This creates a problem, because what is essential depends not only on the local model fragment, but also on the context of the model and its usage, i .e. the structure of the entire system and the task to be performed. For instance, in diagnosis the goal of discriminating between different behavior modes determines the distinctions to be made . The paper deals with the problem of deriving the sets of qualitative values of model variables that allow to generate the distinctions required by the goal of model based prediction and the structure of the system . We present a formal definition and analysis of the problem and an algorithm for computing appropriate qualitative values based on propagation of distinctions . An important special case is the computation of local landmarks of variables . Based on the generic solution, we show how models for diagnostic can be derived .