A method for semi-automatic explicitation of agent's behavior: application to the study of an immersive driving simulator

Kevin Darty (1) , Julien Saunier (2) , Nicolas Sabouret (3)

1 IFSTTAR/COSYS/LEPSIS - Laboratoire Exploitation, Perception, Simulateurs et Simulations
2 LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes
3 LIMSI - Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur

This paper presents a method for evaluating the credibility of agents' behaviors in immersive multi-agent simulations. It combines two approaches. The first one is based on a qualitative analysis of questionnaires filled by the users and annotations filled by others participants to draw categories of users (related to their behavior in the context of the simulation or in real life). The second one carries out a quantitative behavior data collection during simulations in order to automatically extract behavior clusters. We then study the similarities between user categories, participants' annotations and behavior clusters. Afterward, relying on user categories and annotations, we compare human behaviors to agent ones in order to evaluate the agents' credibility and make their behaviors explicit. We illustrate our method with an immersive driving simulator experiment.

Mots clés: multi-agent simulation; credibility evaluation; objective and subjective approach; behavior clustering and explicitation

Domaines: Intelligence artificielle [cs.AI]

Kevin Darty, Julien Saunier, Nicolas Sabouret. A method for semi-automatic explicitation of agent's behavior: application to the study of an immersive driving simulator. International Conference on Agents and Artificial Intelligence (ICAART), Mar 2014, Angers, France. pp.81-91. ⟨hal-00985300⟩