Relevance Reasoning to Guide Compositional Modeling

Reference: Levy, A. Y.; Iwasaki, Y.; & Motoda, H. Relevance Reasoning to Guide Compositional Modeling. Seoul, Korea, 1992.

Abstract: The ability to choose an appropriate manner in which to model a given device is crucial in making a compositional modeling [FF91] approach successful. In compositional modeling, a system is provided with a library of composible pieces of knowledge about the physical world, called model fragments, each representing a conceptually distinct phenomenon such as a physical process or one aspect of a component behavior. Given a specific query about a device, the sytem chooses among those model fragments to compose a model of the device that is nost adequate to answer the query. Selection of appropriate model fragments can be viewed as a special case of a more general problem of reasoning about relevance of knowledge to a given goal. In this paper we pursue this view by applying a general framework for reasoning about relevance to the problem of model fragment selection. We show that heuristics for model selection can be usefully stated as irrelevance claims.

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