Scale-Based Monotonicity Analysis in Qualitative Modelling with Flat Segments

Brooks, Martin and Yan, Yuhong and Lemire, Daniel (2005) Scale-Based Monotonicity Analysis in Qualitative Modelling with Flat Segments. [Conference Paper]

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Qualitative models are often more suitable than classical quantitative models in tasks such as Model-based Diagnosis (MBD), explaining system behavior, and designing novel devices from first principles. Monotonicity is an important feature to leverage when constructing qualitative models. Detecting monotonic pieces robustly and efficiently from sensor or simulation data remains an open problem. This paper presents scale-based monotonicity: the notion that monotonicity can be defined relative to a scale. Real-valued functions defined on a finite set of reals e.g. sensor data or simulation results, can be partitioned into quasi-monotonic segments, i.e. segments monotonic with respect to a scale, in linear time. A novel segmentation algorithm is introduced along with a scale-based definition of "flatness".

Item Type:Conference Paper
Keywords:Piecewise Quasi-Monotone Functions, Model-Based Diagnostic, Qualitative Model Abstraction
Subjects:Computer Science > Artificial Intelligence
ID Code:4495
Deposited By: Lemire, Daniel
Deposited On:06 Aug 2005
Last Modified:11 Mar 2011 08:56


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