MASCARET: A Pedagogical Multi-Agent System for Virtual Environments for Training
Cédric Buche (CERV/ENIB, France), Ronan Querrec (CERV/ENIB, France), Pierre De Loor (CERV/ENIB, France) and Pierre Chevaillier (CERV/ENIB, France)
Copyright © 2008.
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This study concerns virtual environments for training in operational conditions. The principal developed idea is that these environments are heterogeneous and open multi-agent systems. The MASCARET model is proposed to organize the interactions between agents and to provide them reactive, cognitive and social abilities to simulate the physical and social environment. The physical environment represents, in a realistic way, the phenomena that learners and teachers have to take into account. The social environment is simulated by agents executing collaborative and adaptive tasks. These agents realize, in team, procedures that they have to adapt to the environment. The users participate to the training environment through their avatar. In this article, we explain how we integrated, in MASCARET, models necessary to the creation of Intelligent Tutoring System. We notably incorporate pedagogical strategies and pedagogical actions. We present pedagogical agents. To validate our model, the SÉCURÉVI application for fire fighters’ training is developed.