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Information Fusion: Frameworks and ArchitecturesContents of the sessionHybrid Artificial Intelligent Systems are widely applied in data fusion solutions with sensor data and high-level representations of situations, adaptation mechanisms or distributed collaborative techniques. Information Fusion systems must face a complex design process to allow the satisfaction of requirements to show robust, context-sensitive behavior, and efficient performance in real time. System designer uses information models and reasoning strategies to process data, and context knowledge about a priori relationships between entities. These aspects should be considered from a methodological perspective, formalizing architectures or frameworks that include these Hybrid Artificial Intelligence Systems inside the high level functionalities. This session concerns with the definition of a general framework for Information Fusion that integrate HAIS for real applications, including the following topics:
ContributionsOriginal contributions are sought in the area of the topics covered by this special session. All submissions will be refereed by at least two experts in the field based on originality, significance, quality and clarity. Accepted contributions are to be published in the HAIS'10 Proceedings. Papers must be prepared according to the LNCS-LNAI styletemplate (see: http://www.springer.de/comp/lncs/authors.html) and must be no more than 8 pages long, including figures and bibliography. NOTICE: At least one author of each accepted paper must register in order for the paper to be included in the HAIS 2010 Proceedings. Authors are requested to submit their contributions through the HAIS'10 paper submission page and also email a copy to the chair of this special session (PDF format). Co-Chairs
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