Cédric Herpson

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This paper introduces a declarative agent-oriented language for Ambient Intelligence – S-CLAIM – that allows programming reactive or cognitive mobile agents in a simple, easy-to-use manner while meeting AmI requirements. Based on a hierarchical representation of the agents, the language offers a natural solution to achieve context-sensitivity. S-CLAIM is(More)
The purpose of a supervision system is to detect, identify and repair any fault that may occur in the system it supervises. Nowadays industrial process are mainly distributed, and their supervision systems are still centralized. Consequently, when communications are disrupted, it slows down or stops the supervision process. Increasing production rates make(More)
The traditional, centralized, approach to supervision is challenged when communications between supervision and supervised systems become either slow, disrupted or too costly. To obtain a supervision system that is able to dynamically adapt itself to the communications' state, we propose to distribute the supervision process through several autonomous(More)
L'avènement de systèmes complexes physique-ment distribués et le besoin d'accroître le taux de disponibilité des services et processus in-dustriels nécessitent la conception de systèmes de supervision distribués. L'approche tradition-nelle de la supervision, centralisée, est en effet remise en question lorsque les communications entre système de supervision(More)
Nous présentons dans cet article un mécanisme d'apprentissage du comportement des appareils électriques dans le contexte d'une maison intel-ligente. L'objectif de ce mécanisme est de ré-duire la consommation d'énergie des appareils à effet différé (par exemple le chauffage) tout en maximisant le confort des habitants. Notre approche utilise un modèle(More)
The capacity to apply knowledge in a context different than the one in which it was learned has become crucial within the area of autonomous agents. This paper specifically addresses the issue of transfer of knowledge acquired through online learning in partially observable environments. We investigate the discovery of relevant abstract concepts which help(More)
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