THE ANALYSIS OF ASSUMPTIONS IN MODEL BASES USING METAGRAPHS

Decision models are often based on certain assumptions as to their val idity. Relevant assumptions may include value-based assumptions, such as limitations on the range or values of some input variables or exoge nous factors, as well as assumptions about model structure (e.g., Line arity). In a model base consisting of many models, there may be severa l models (or collections of models) that can be used to solve a partic ular problem. We may wish to know what the applicable models are, what assumptions are associated with these models, and whether a given set of assumptions is necessary and/or sufficient for solving the problem . We describe an analytical approach, based on a graph-theoretic const ruct called a metagraph, and show how it can be used to represent and analyze assumptions in model bases.