Yan, Brooks and Lemire (2005) Scale-Based Monotonicity Analysis in Qualitative Modelling with Flat Segments

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Scale-Based Monotonicity Analysis in Qualitative Modelling with Flat Segments

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CONTRIBUTORS:

	Author:	Yan, Yuhong
	Author:	Brooks, Martin
	Author:	Lemire, Daniel (Université du Québec à Montréal (UQAM))

PROCEEDINGS TITLE:

IJCAI05

YEAR:

2005

PUB TYPE:

Conference Paper in Proceedings

PAGES:

9999 - 9999

SUBJECT(S):

Piecewise Quasi-Monotone Functions, Model-Based Diagnostic, Qualitative Model Abstraction

DISCIPLINE:

Computer Science

HTTP:

http://www.ondelette.com/lemire/abstracts/IJCAI05.html

LANGUAGE:

English

PUB ID:

103-414-629 (Last edited on 2005/04/09 06:06:48 GMT-6)

SPONSOR(S):

ABSTRACT:
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".

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