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Tractable approximate knowledge fusion using the Horn fragment of serial propositional dynamic logic
2010 (English)In: International Journal of Approximate Reasoning, ISSN 0888-613X, E-ISSN 1873-4731, Vol. 51, no 3, 346-362Artikel i tidskrift (Refereed) Published
Abstract [en]

In this paper we investigate a technique for fusing approximate knowledge obtained from distributed, heterogeneous information sources. This issue is substantial, e.g., in modeling multiagent systems, where a group of loosely coupled heterogeneous agents cooperate in achieving a common goal. Information exchange, leading ultimately to knowledge fusion, is a natural and vital ingredient of this process. We use a generalization of rough sets and relations [30], which depends on allowing arbitrary similarity relations. The starting point of this research is [6], where a framework for knowledge fusion in multiagent systems is introduced. Agents individual perceptual capabilities are represented by similarity relations, further aggregated to express joint capabilities of teams, This aggregation, expressing a shift from individual to social level of agents activity, has been formalized by means of dynamic logic. The approach of Doherty et al. (2007) [6] uses the full propositional dynamic logic, which does not guarantee tractability of reasoning. Our idea is to adapt the techniques of Nguyen [26-28] to provide an engine for tractable approximate database querying restricted to a Horn fragment of serial dynamic logic. We also show that the obtained formalism is quite powerful in applications.

Keyword [en]
Rough sets, Similarity relation, Dynamic logic, Knowledge fusion, Approximate database
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-54706 (URN)10.1016/j.ijar.2009.11.002 (DOI)000275610600005 (ISI)oai:DiVA.org:liu-54706 (OAI)
Available from2010-04-06 Created:2010-04-06 Last updated:2011-02-24

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Dunin-Keplicz, BarbaraAnh Nguyen, LinhSzalas, Andrzej
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University of WarsawKPLAB - Knowledge Processing LabThe Institute of Technology
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International Journal of Approximate Reasoning
Engineering and Technology

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