Behavior Clustering and Explicitation for the Study of Agents’ Credibility: Application to a Virtual Driver Simulation

  • Kévin DartyEmail author
  • Julien Saunier
  • Nicolas Sabouret
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8946)


The aim of this article is to provide a method for evaluating the credibility of agents’ behaviors in immersive multi-agent simulations. It is based on a quantitative data collection from both humans and agents simulation logs during an experiment. These data allow us to semi-automatically extract behavior clusters. In order to obtain explicit information about the behaviors, we analyze questionnaires filled by the users and annotations filled by a second set of participants. It enables to draw user categories related to their behavior in the context of the simulation or of their real life habits. We then study the similarities between behavior clusters, user categories, and participants’ annotations. Afterwards, we evaluate the agents’ credibility and make their behaviors explicit by comparing human behaviors to agent ones according to user categories and annotations. Our method is applied to the study of virtual driver simulation through an immersive driving simulator.


Multi-agent simulation Behavior clustering Credibility evaluation 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Kévin Darty
    • 1
    Email author
  • Julien Saunier
    • 2
  • Nicolas Sabouret
    • 3
  1. 1.Laboratory for Road Operations, Perception, Simulators and SimulationsFrench Institute of Science and Technology for Transport, Development and NetworksMarne la ValléeFrance
  2. 2.Computer Science, Information Processing and Systems LaboratoryNational Institute of Applied Sciences of RouenSaint-étienne-du-rouvray CedexFrance
  3. 3.Computer Sciences Laboratory for Mechanics and Engineering Sciences, National Center for Scientific ResearchParis-Sud UniversityOrsay CedexFrance

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