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Fusing Approximate Knowledge from Distributed Sources
2009 (English)In: Proceedings of the 3rd International Symposium on Intelligent Distributed Computing (IDC), Springer Berlin/Heidelberg, 2009, Vol. 237, 75-86Conference paper (Refereed)
Abstract [en]

In this paper we investigate a technique for fusing approximate knowledge obtained from distributed, heterogeneous information sources. We use a generalization of rough sets and relations [14], which depends on allowing arbitrary similarity relations. The starting point of this research is [2], where a framework for knowledge fusion in multi-agent systems is introduced. Agent’s individual perceptual capabilities are represented by similarity relations, further aggregated to express joint capabilities of teams. This aggregation, allowing a shift from individual to social level, has been formalized by means of dynamic logic. The approach of [2] uses the full propositional dynamic logic, not guaranteeing the tractability of reasoning. Therefore the results of [11, 12, 13] are adapted to provide a technical engine for tractable approximate database querying restricted to a Horn fragment of serial PDL. We also show that the obtained formalism is quite powerful in applications.

Series
Studies in Computational Intelligence, ISSN 1860-949X ; 237
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-74987 (URN)10.1007/978-3-642-03214-1_8 (DOI)978-3-642-03213-4 (ISBN)978-3-642-26930-1 (ISBN)oai:DiVA.org:liu-74987 (OAI)diva2:499763 (DiVA)
Conference
3rd International Symposium on Intelligent Distributed Computing (IDC), Ayia Napa, Cyprus, October, 2009
Available from2012-02-13 Created:2012-02-13 Last updated:2012-02-21

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Dunin-Keplicz, BarbaraNguyen, Linh AnhSzalas, Andrzej
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Warsaw UniversityKPLAB - Knowledge Processing LabThe Institute of Technology
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