Multiagent Systems for Virtual Environment for Training. Application to Fire-Fighting

Abstract

This study concerns virtual environments for training in operational conditions. The principal developed idea is that these environments are heterogeneous and open multiagent systems. The MASCARET model is proposed to organize the interactions between agents and to give 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. They realize, in team, procedures that they have to adapt to the environment. Users participate to the training environment through their avatar. To validate our model, the SECUREVI application for fire-fighters training is developed.

GASPAR : Aviation Management on an Aircraft Carrier Using Virtual Reality

“…). To do that, we propose the MASCARET 3 [5] model. This model describes concepts that refer to organizations and procedures by interpreting UML metamodel semantics.…”

Virtual tyre production: Learning industrial process through an Informed Virtual Environment

“…A welding simulator developed for the AFPA (French association for technical learning) named CS-Wave [3] trains the user the technical gesture and improves their understanding of the invisible phenomena in the real world. Arvi [4] allows fire fighters to be immersed in a fire or a catastrophe crisis through a virtual environment. Fiacre [5] is a system where high speed train drivers are trained on railway interventions.…”

Modeling of Errors Realized by a Human Learner in Virtual Environment for Training

“…Our existing ITS as proposed in [2] bases on the model MASCARET [1] where we used an multi-agent system to simulate collaboration between human learners and agents during their realization of tasks. Learners are gathered in team consisting of several predefined roles, every role contains a number of tasks associated eventually with accurate resources, every leaner also owns an epistemic memory containing all actions realized in the past, etc.…”

“…In order to simulate procedural and collaborative work, we developed the model MASCARET (Multi-Agent System for Collaborative Adaptive and Realistic Environment for Training) where human learners and agents collaborate to realize a task [1]. Learners are gathered in team consisting of several predefined roles, every role contains a number of actions to be realized by learners with specific resources.…”