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Download PDFOpen PDF in browserMeasuring Disagreement among Knowledge BasesEasyChair Preprint 21814 pages•Date: June 1, 2018AbstractWhen combining beliefs from different sources, often not only new knowledge but also conflicts arise. In this paper, we investigate how we can measure the disagreement among sources. We start our investigation with disagreement measures that can be induced from inconsistency measures in an automated way. After discussing some problems with this approach, we propose a new measure that is inspired by the $\eta$-inconsistency measure. Roughly speaking, it measures how well we can satisfy all sources simultaneously. We show that the new measure satisfies desirable properties, scales well with respect to the number of sources and illustrate its applicability in inconsistency-tolerant reasoning. Keyphrases: Inconsistency measures, Inconsistency-tolerant reasoning, belief merging, disagreement measure Download PDFOpen PDF in browser |
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