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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Semantic Reasoning with Uncertain Information from Unreliable Sources
verfasst von : Murat Şensoy, Lance Kaplan, Geeth de Mel
Erschienen in: PRIMA 2016: Principles and Practice of Multi-Agent Systems
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Abstract
Intelligent software agents may significantly benefit from semantic reasoning. However, existing semantic reasoners are based on Description Logics, which cannot handle vague, incomplete, and unreliable knowledge. In this paper, we propose \(\mathcal {S}\textsf {DL}\text {-}\textsf {Lite}\) which extends \(\textsf {DL}\text {-}\textsf {Lite}_{{R}}\) with subjective opinions to represent uncertainty in knowledge. We directly incorporate trust into the reasoning so that the inconsistencies in the knowledge can be resolved based on trust evidence analysis. Therefore, the proposed logic can handle uncertain information from unreliable sources. We demonstrate how \(\mathcal {S}\textsf {DL}\text {-}\textsf {Lite}\) can be used for semantic fusion of uncertain information from unreliable sources and show that \(\mathcal {S}\textsf {DL}\text {-}\textsf {Lite}\) reasoner can estimate the ground truth with a minimal error.