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Detecting Inconsistencies in Rule-Based Reasoning for Ambient Intelligence

Authors: Hamdi Aloulou; Romain Endelin; Mounir Mokhtari; Bessam Abdulrazak; Firas Kaddachi; Joaquim Bellmunt;

Detecting Inconsistencies in Rule-Based Reasoning for Ambient Intelligence

Abstract

Rule-based reasoning engines have proven their value for Context-Awareness in Ambient Intelligence. However, the definition of rules is often prone to human-caused inconsistencies or sensor failures. In this paper, we propose to assist the definition of rules for context-awareness by automatically validating the consistency of the rules. Using our approach, we are able to detect conflicts between rules for context-awareness, as well as recommend adding sensors to improve the reasoner outcomes. We propose to define rules as a finite set of conditions to be verified, and provide consistency-checking capabilities to these conditions. We discuss in this paper our approach as well as results and validation.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
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