The analysis of assumptions in model bases using metagraphs

The analysis of assumptions in model bases using metagraphs

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Article ID: iaor2000356
Country: United States
Volume: 44
Issue: 7
Start Page Number: 982
End Page Number: 995
Publication Date: Jul 1998
Journal: Management Science
Authors: ,
Keywords: information, decision: studies, networks
Abstract:

Decision models are often based on certain assumptions as to their validity. Relevant assumptions may include value-based assumptions, such as limitations on the range or values of some input variables or exogenous factors, as well as assumptions about model structure (e.g., linearity). In a model base consisting of many models, there may be several models (or collections of models) that can be used to solve a particular 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 construct called a metagraph, and show how it can be used to represent and analyze assumptions in model bases.

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