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)
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 , which depends on allowing arbitrary similarity relations. The starting point of this research is , 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  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.
Studies in Computational Intelligence, ISSN 1860-949X ; 237
National CategoryEngineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-74987DOI: 10.1007/978-3-642-03214-1_8ISBN: 978-3-642-03213-4ISBN: 978-3-642-26930-1OAI: oai:DiVA.org:liu-74987DiVA: diva2:499763
3rd International Symposium on Intelligent Distributed Computing (IDC), Ayia Napa, Cyprus, October, 2009