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Contextual Argumentation in Ambient Intelligence

  • Conference paper
Logic Programming and Nonmonotonic Reasoning (LPNMR 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5753))

Abstract

The imperfect nature of context in Ambient Intelligence environments and the special characteristics of the entities that possess and share the available context information render contextual reasoning a very challenging task. Most current Ambient Intelligence systems have not successfully addressed these challenges, as they rely on simplifying assumptions, such as perfect knowledge of context, centralized context, and unbounded computational and communicating capabilities. This paper presents a knowledge representation model based on the Multi-Context Systems paradigm, which represents ambient agents as autonomous logic-based entities that exchange context information through mappings, and uses preference information to express their confidence in the imported knowledge. On top of this model, we have developed an argumentation framework that exploits context and preference information to resolve conflicts caused by the interaction of ambient agents through mappings, and a distributed algorithm for query evaluation.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, FO.R.T.H., Vassilika Voutwn, P.O. Box 1385, GR, 71110, Heraklion, Greece

    Antonis Bikakis & Grigoris Antoniou

Authors
  1. Antonis Bikakis
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  2. Grigoris Antoniou
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Editor information

Editors and Affiliations

  1. Faculty of Engineering and Natural Sciences, Sabanci University, Orhanli, Tuzla, 34956, Istanbul, Turkey

    Esra Erdem

  2. Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay,, Hong Kong

    Fangzhen Lin

  3. Institut für Informatik, Universität Potsdam, August-Bebel-Str. 89, D-14482, Potsdam, Germany

    Torsten Schaub

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© 2009 Springer-Verlag Berlin Heidelberg

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Bikakis, A., Antoniou, G. (2009). Contextual Argumentation in Ambient Intelligence. In: Erdem, E., Lin, F., Schaub, T. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2009. Lecture Notes in Computer Science(), vol 5753. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04238-6_6

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  • DOI: https://doi.org/10.1007/978-3-642-04238-6_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04237-9

  • Online ISBN: 978-3-642-04238-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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