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Monotone Pieces Analysis for Qualitative Modeling

Yan, Yuhong and Lemire, Daniel and Brooks, Martin (2004) Monotone Pieces Analysis for Qualitative Modeling. [Conference Paper]

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Abstract

It is a crucial task to build qualitative models of industrial applications for model-based diagnosis. A Model Abstraction procedure is designed to automatically transform a quantitative model into qualitative model. If the data is monotone, the behavior can be easily abstracted using the corners of the bounding rectangle. Hence, many existing model abstraction approaches rely on monotonicity. But it is not a trivial problem to robustly detect monotone pieces from scattered data obtained by numerical simulation or experiments. This paper introduces an approach based on scale-dependent monotonicity: the notion that monotonicity can be defined relative to a scale. Real-valued functions defined on a finite set of reals e.g. simulation results, can be partitioned into quasi-monotone segments. The end points for the monotone segments are used as the initial set of landmarks for qualitative model abstraction. The qualitative model abstraction works as an iteratively refining process starting from the initial landmarks. The monotonicity analysis presented here can be used in constructing many other kinds of qualitative models; it is robust and computationally efficient.

Item Type:Conference Paper
Keywords:Piecewise Quasi-Monotone Functions, Model-Based Diagnostic, Qualitative Model Abstraction
Subjects:Computer Science > Artificial Intelligence
ID Code:4493
Deposited By:Lemire, Daniel
Deposited On:06 Aug 2005
Last Modified:11 Mar 2011 08:56

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