Compositional Modelling (CM) has been applied to synthesize automatically plausible scenarios in many problem domains with promising results. However, it is assumed that the generic and reusable model fragments within the knowledge base can all be expressed by precise and crisp information. This paper presents an initial attempt to extend the existing CM work to allow the generation of scenario spaces which are capable of representing, storing and supporting inference about imprecise or ill-defined data, by the use of fuzzy sets. A knowledge representation formalism for both fuzzy parameters and fuzzy constraints is incorporated into the representation of conventional model fragments. The applicability of the proposed method is illustrated by means of a simple worked example for supporting crime investigation.
|Number of pages||6|
|Publication status||Published - 23 Jul 2007|