Specification of Interlevel Relations for Agent Models in Multiple Abstraction Dimensions

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Multiagent systems for a certain application area can be modelled at multiple levels of abstraction. Interlevel relations are a means to relate models from different abstraction levels. Three dimensions of abstraction often occurring are the process abstraction, temporal abstraction, and agent cluster abstraction dimension. In this paper a unifying formalisation is presented that can be used as a framework to specify interlevel relations for any of such dimensions. The approach is illustrated by showing how a variety of different types of abstraction relations between multi-agent system models can be formally specified in a unified manner. © 2011 Springer-Verlag.
Original languageEnglish
Title of host publicationProceedings of the 24th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE’11, Part II.
EditorsK.G. Mehrotra et al.
Place of PublicationBerlin-Heidelberg
PublisherSpringer Verlag
Pages542-555
Number of pages14
DOIs
Publication statusPublished - 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6704 LNAI

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Multi agent systems
Specifications

Keywords

  • abstraction dimension
  • interlevel relation

Cite this

Treur, J. (2011). Specification of Interlevel Relations for Agent Models in Multiple Abstraction Dimensions. In K. G. Mehrotra et al. (Ed.), Proceedings of the 24th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE’11, Part II. (pp. 542-555). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6704 LNAI). Berlin-Heidelberg: Springer Verlag. https://doi.org/10.1007/978-3-642-21827-9_55
Treur, J. / Specification of Interlevel Relations for Agent Models in Multiple Abstraction Dimensions. Proceedings of the 24th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE’11, Part II.. editor / K.G. Mehrotra et al. Berlin-Heidelberg : Springer Verlag, 2011. pp. 542-555 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Treur, J 2011, Specification of Interlevel Relations for Agent Models in Multiple Abstraction Dimensions. in KG Mehrotra et al. (ed.), Proceedings of the 24th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE’11, Part II.. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6704 LNAI, Springer Verlag, Berlin-Heidelberg, pp. 542-555. https://doi.org/10.1007/978-3-642-21827-9_55

Specification of Interlevel Relations for Agent Models in Multiple Abstraction Dimensions. / Treur, J.

Proceedings of the 24th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE’11, Part II.. ed. / K.G. Mehrotra et al. Berlin-Heidelberg : Springer Verlag, 2011. p. 542-555 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6704 LNAI).

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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Treur J. Specification of Interlevel Relations for Agent Models in Multiple Abstraction Dimensions. In Mehrotra et al. KG, editor, Proceedings of the 24th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE’11, Part II.. Berlin-Heidelberg: Springer Verlag. 2011. p. 542-555. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-21827-9_55