Defining and Modeling Context in a Multi-Agent Systems Architecture for Decision-Making

Abstract : Ambient intelligence involves the convergence of several computing areas: ubiquitous computing, intelligent systems and context-awareness. Developing context-aware applications needs facilities for recognizing and representing context, reasoning on it and adapting to it accordingly. In what concerns context representation, the newest and most challenging representation is the ontological one. The problem is that current ontologies for context do not provide a standard for representing complex context attributes. In this paper, we propose a context definition and representation used to construct context-based agent architecture. The representation we propose combines the generality provided by ontologies with the complexity inspired by the object oriented models. The goal of the proposed architecture is to support the deployment of context-aware agents able to learn how to recognize the context of their decisions and to adapt to it. The use of this architecture is illustrated on a test MAS for agenda management, using the JADE-LEAP platform on PCs and PDAs.
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Article dans une revue
CiteSeerx, 2009
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https://hal-emse.ccsd.cnrs.fr/emse-00674907
Contributeur : Florent Breuil <>
Soumis le : mardi 28 février 2012 - 14:21:04
Dernière modification le : mardi 23 octobre 2018 - 14:36:03

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  • HAL Id : emse-00674907, version 1

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Oana Bucur, Philippe Beaune, Olivier Boissier. Defining and Modeling Context in a Multi-Agent Systems Architecture for Decision-Making. CiteSeerx, 2009. 〈emse-00674907〉

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