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 advent of complex and physically distributed systems and the need to minimize the down-time of services and production processes call for more efficient supervision systems. Traditionally centralized, the anytime supervision of such systems is challenged when communications between the supervision and the supervised systems become either slow, disrupted(More)
In this paper we propose a learning mechanism to build the behavior of electrical appliances in a smart home context. The aim of that mechanism is to reduce the consumption of appliances whose effect is delayed (for example the heating) while maximizing the inhabitants comfort. Our approach is based on a predictive model of home humans’ activities. That(More)
Azizi Ab Aziz Lucas Agussurja Jean-Paul Arcangeli Tim Baarslag Dirk Bade Bruno Beaufils Francesco Belardinelli Karel Bergmann Stefano Bromuri Suratna Budalakoti Sofia Ceppi Kyriakos Chatzidimitriou Antonios Chrysopoulos Zijie Cong Jorge Pablo Cordero Hernandez Lennard de Rijk David DeAngelis John Debenham Fabien Delecroix Marc Esteva Patricia Everaere Moser(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)
The capacity to apply knowledge in a context different than the one in which it was learned is still an open research question within the area of learning agents. This paper specifically addresses the issue of transfer of knowledge acquired through online learning in a partially observable environment characterized by its 2D geographical configuration. We(More)
The advent of physically distributed systems and the need to minimize the down-time of services and production processes require more efficient supervision systems. Traditionally centralized, the anytime supervision of such systems is challenged when communications between supervision and supervised systems become slow, disrupted or too costly. Distributing(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)
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)
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