Hybrid system to analyze user's behaviour

Valérian Guivarch (1) , Juan Francisco De Paz Santana (2) , Gabriel Villarrubia (2) , Javier Bajo (3) , André Péninou (4, 5) , Valérie Camps (1, 6)

1 IRIT-SMAC - Systèmes Multi-Agents Coopératifs
2 Universidad de Salamanca
3 UPM - Universidad Politécnica de Madrid
4 IRIT-SIG - Systèmes d’Informations Généralisées
5 UT2J - Université Toulouse - Jean Jaurès
6 UT3 - Université Toulouse III - Paul Sabatier

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.

Mots clés: Ambient intelligence; Multi-agent systems; Classifiers

Domaines: Système multi-agents [cs.MA]

Valérian Guivarch, Juan Francisco De Paz Santana, Gabriel Villarrubia, Javier Bajo, André Péninou, et al.. Hybrid system to analyze user's behaviour. IEEE Symposium Series on Computational Intelligence (SSCI 2016), Dec 2016, Athens, Greece. pp. 1-5. ⟨hal-01736261⟩