| Summary: | The concept of a generalized model management System (GMMS) and its role in a decision support system are discussed. A paradigm for developing a GMMS which integrates artificial intelligence techniques with data management concepts is presented. The paradigm views a GMMS as a knowledge-based modeling system (KBMS) with knowledge abstractions as the vehicle of knowledge and model representation. Knowledge abstractions are introduced as a hybrid of the predicate calculus, semantic network, and frame representations in artificial intelligence (AI) embodied in an equivalent of a programming language data abstraction structure. As a result, models represented by knowledge abstractions are not only subject to the powerful problem reduction and inference techniques available in the AI domain but are also in a form conducive to model management. The knowledge abstraction in its most general form is seen as a frame which serves as a template for generating abstraction instances for specific classes of models. The corollaries of an abstraction-based GMMS with current data management concepts are explored. A CODASYL implementation of an abstraction-based GMMS for the class of linear programming models is described and demonstrated.
|
|---|
