Dynamic Filtering of Useless Data in an Adaptive Multi-Agent System : Evaluation in the Ambient Domain

National audienceAmadeus is an Adaptive Multi-Agent System whose goal is to observe and to learn users’ behaviour in an ambient system in order to perform their recurrent actions on their behalf. Considering the large number of devices (data sources) that generally compose ambient systems, performing an efficient learning in such a domain requires filtering useless data. This paper focuses on an extended version of Amadeus taking account this requirement and proposes a solution based on cooperative interactions between the different agents composing Amadeus. An evaluation of the performances of our system as well as the encouraging obtained results are then shown

A Cooperative SoS Architecting Approach Based On Adaptive Multi-Agent Systems.

This paper focuses on Systems of Systems (SoS) modeling and architecting. SoS architecting deals with the way that independent components of a SoS can be dynamically structured and can change autonomously their interactions in an efficient manner to fulfill the goal of the SoS and to cope with an evolving environment. In this context we defined a new model called SApHESIA (SoS Architecting HEuriStIc based on Agents) focusing on the environment and its dynamics. We also proposed a cooperative heuristic to control interactions exchanges between components. These contributions are then instantiated to a case study and evaluated through two scenarii. Obtained results are finally discussed and some perspectives are given

Hybrid system to analyze user's behaviour

The evolution of ambient intelligence systems has allowed for the development of adaptable systems. These systems trace user's habits in an automatic way and act accordingly, resulting in a context aware system. The goal is to make these systems adaptable to the user's environment, without the need for their direct interaction. This paper proposes a system that can learn from users' behavior. In order for the system to perform effectively, an adaptable multi agent system is proposed and the results are compared with the use of several classifiers

A Cooperative Multi-Agent System for Crowd Sensing Based Estimation in Smart Cities

The concept of Smart City has spread as a solution to ensure better access to information and services to citizens, but also as a means to reduce the environmental footprint of cities. To this end, a continuous and wide observation of the environment is necessary to analyze information that enables government bodies to act on the environment appropriately. Moreover, a diffused acquisition of information requires adequate infrastructure and proper devices, which results in relevant installation and maintenance costs. Our proposal enables reducing the number of necessary sensors to be deployed while ensuring that information is available at any time and anywhere. We present the HybridIoT system to cope with the lack of environmental information in the urban context through an estimation technique that integrates heterogeneous data acquired from some different sensors. HybridIoT can be deployed in large-scale contexts and ensures data accessibility even if devices enter or leave the system at any time and everywhere. We compare the results to those obtained by state-of-the-art techniques to assess the validity of our proposal, in particular concerning the properties of openness, large-scale, and heterogeneity, of primary importance in the context of the development of systems to be deployed in the smart city context

Learning user's behaviour with an Adaptive Multi-Agent System approach

The context-aware systems allow the adaptation of the environment, which depends on the values perceived by sensors and on the users’ preferences detected from users behaviour. These system need to adapt at the users’ preferences change so as to generate dynamic systems that improve their models while they are running. This work proposes a multi-agent system which allows to learn and to anticipate users’ behaviour and to adapt at the change into a dynamic mode, and where storing information from the previous cases during successive execution is no more compulsory

Regards d’enseignants québécois sur les élèves doués : points de vue diversifiés

This study examines teachers’ perceptions of gifted students in their class, in a Quebec school service centre, and the influence of personal and contextual variables. The sample consists of 21 primary school teachers (18 women and 3 men). After the lexical analysis carried out with the Alceste software, four specific classes of statements emerge from the teachers’ discourse. In addition, age, teaching cycle, type of class, number of years of experience, involvement in an intervention plan and experience with giftedness predict the heterogeneity of the perceptions of teachers towards giftedness. The results suggest more traditional and stereotypical perceptions of giftedness by teachers. Keywords: perceptions, representations, teachers, giftedness, characteristics, high potential, lexical analysisCette étude s’intéresse aux perceptions des enseignants concernant les élèves doués de leur classe, dans un centre de services scolaire québécois, et à l’influence de certaines variables personnelles et contextuelles sur ces perceptions. L’échantillon se compose de 21 enseignants du primaire (18 femmes et 3 hommes). À l’issue de l’analyse lexicale réalisée avec le logiciel Alceste, quatre classes d’énoncés spécifiques se dégagent du discours des enseignants. L’âge, le cycle d’enseignement, le type de classe, le nombre d’années d’expérience, l’implication dans un plan d’intervention et l’expérience envers la douance constituent des facteurs explicatifs de l’hétérogénéité des perceptions des enseignants envers la douance. Les résultats portent également à croire que des perceptions plus traditionnelles et stéréotypées de la douance persistent chez certains enseignants. Mots-clés : perceptions, représentations, enseignants, douance, caractéristiques, haut potentiel, analyse lexical

Projet INCOME : INfrastructure de gestion de COntexte Multi-Echelle pour l'Internet des Objets

International audienceCet article donne un aperçu du projet de recherche INCOME financé par l'Agence Nationale de la Recherche française en décrivant la fiche d'identité du projet, ses principaux enjeux scientifiques ainsi que les premiers résultats obtenus

Analysis of altruistic behaviors in multi-agent systems

International audienc

Attitudes coopératives individuelles pour l'adaptation collective

International audienceLe concept de coopération est souvent lié à la résolution distribuée de problèmes. Il prend une signification plus large dès lors qu'on l'utilise pour dire qu'un système est dans une situation coopérative. Il signifie toujours coopération pour la résolution du problème auquel est confronté le système, mais aussi coopération entre les entités du système, en l'occurrence les agents, pour que le système ait un fonctionnement optimal. Dans notre approche, la coopération caractérise l'activité globale d'un système. Ce papier rend compte des situations qui modifient négativement le fonctionnement du système et qui rompent l'état de coopération : elles sont dites non coopératives. Le but du concepteur du système multi-agent est de doter les agents d'attitudes coopératives individuelles et de règles générales de comportement leur permettant de détecter et de traiter ces situations non désirées. Ces règles sont décrites dans le cadre général et instanciées pour le domaine d'application choisi, en l'occurrence le monde des pavés ou "tileworld". Grâce à l'existence du collectif, les agents peuvent s'adapter à ces situations difficilement prévisibles du fait de la complexité des systèmes multi-agents. Les résultats fournis par l'application montrent que l'attitude coopérative des agents entraîne un meilleur fonctionnement global du système