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2015 Volume 30
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RESEARCH ARTICLE   Open Access    

Resolving conflicts in knowledge for ambient intelligence

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  • Abstract: Ambient intelligence (AmI) proposes pervasive information systems composed of autonomous agents embedded within the environment who, in orchestration, complement human activity in an intelligent manner. As such, it is an interesting and challenging application area for many computer science fields and approaches. A critical issue in such application scenarios is that the agents must be able to acquire, exchange, and evaluate knowledge about the environment, its users, and their activities. Knowledge populated between the agents in such systems may be contextually dependent, ambiguous, and incomplete. Conflicts may thus naturally arise, that need to be dealt with by the agents in an autonomous way. In this survey, we relate AmI to the area of knowledge representation and reasoning (KR), where conflict resolution has been studied for a long time. We take a look at a number of KR approaches that may be applied: context modelling, multi-context systems, belief revision, ontology evolution and debugging, argumentation, preferences, and paraconsistent reasoning. Our main goal is to describe the state of the art in these fields, and to draw attention of researchers to important theoretical issues and practical challenges that still need to be resolved, in order to reuse the results from KR in AmI systems or similar complex and demanding applications.
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    Martin Homola, Theodore Patkos, Giorgos Flouris, Ján Šefránek, Alexander Šimko, Jozef Frtús, Dimitra Zografistou, Martin Baláž. 2015. Resolving conflicts in knowledge for ambient intelligence. The Knowledge Engineering Review 30(5)455−513, doi: 10.1017/S0269888915000132
    Martin Homola, Theodore Patkos, Giorgos Flouris, Ján Šefránek, Alexander Šimko, Jozef Frtús, Dimitra Zografistou, Martin Baláž. 2015. Resolving conflicts in knowledge for ambient intelligence. The Knowledge Engineering Review 30(5)455−513, doi: 10.1017/S0269888915000132

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RESEARCH ARTICLE   Open Access    

Resolving conflicts in knowledge for ambient intelligence

The Knowledge Engineering Review  30 2015, 30(5): 455−513  |  Cite this article

Abstract: Abstract: Ambient intelligence (AmI) proposes pervasive information systems composed of autonomous agents embedded within the environment who, in orchestration, complement human activity in an intelligent manner. As such, it is an interesting and challenging application area for many computer science fields and approaches. A critical issue in such application scenarios is that the agents must be able to acquire, exchange, and evaluate knowledge about the environment, its users, and their activities. Knowledge populated between the agents in such systems may be contextually dependent, ambiguous, and incomplete. Conflicts may thus naturally arise, that need to be dealt with by the agents in an autonomous way. In this survey, we relate AmI to the area of knowledge representation and reasoning (KR), where conflict resolution has been studied for a long time. We take a look at a number of KR approaches that may be applied: context modelling, multi-context systems, belief revision, ontology evolution and debugging, argumentation, preferences, and paraconsistent reasoning. Our main goal is to describe the state of the art in these fields, and to draw attention of researchers to important theoretical issues and practical challenges that still need to be resolved, in order to reuse the results from KR in AmI systems or similar complex and demanding applications.

    • The authors would like to thank Antonis Bikakis, Luciano Serafini, and Stefan Woltran who provided some very useful feedback on the preliminary version of this survey. The authors would also like to thank Júlia Pukancová and Daniel Skalický for help with proofreading. This work resulted from the Slovak–Greek bilateral project ‘Multi-context Reasoning in Heterogeneous Environments’, registered on the Slovak side under no. SK-GR-0070-11 with the APVV agency and co-financed by the Greek General Secretariat of Science and Technology and the European Union. It was further partially supported from the Slovak national VEGA project no. 1/1333/12 and also from the EU FP7 project DIACHRON (ICT-2011.4.3, #601043).

    • Online solver for DeLP: http://lidia.cs.uns.edu.ar/delp_client/

    • © Cambridge University Press, 2015 2015Cambridge University Press
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    Cite this article
    Martin Homola, Theodore Patkos, Giorgos Flouris, Ján Šefránek, Alexander Šimko, Jozef Frtús, Dimitra Zografistou, Martin Baláž. 2015. Resolving conflicts in knowledge for ambient intelligence. The Knowledge Engineering Review 30(5)455−513, doi: 10.1017/S0269888915000132
    Martin Homola, Theodore Patkos, Giorgos Flouris, Ján Šefránek, Alexander Šimko, Jozef Frtús, Dimitra Zografistou, Martin Baláž. 2015. Resolving conflicts in knowledge for ambient intelligence. The Knowledge Engineering Review 30(5)455−513, doi: 10.1017/S0269888915000132
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