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The New Era of High-Functionality Interfaces Read chapter Read first chapter

2015 | OriginalPaper | Chapter

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

Authors : Kévin Darty, Julien Saunier, Nicolas Sabouret

Published in: Agents and Artificial Intelligence

Publisher: Springer International Publishing

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Abstract

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.

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previous chapter Design and Simulation of a Low-Resource Processing Platform for Mobile Multi-agent Systems in Distributed Heterogeneous Networks
next chapter Knowledge Gradient for Online Reinforcement Learning
Footnotes
1
except for the human or simulated agent question which is not related to the adopted behavior.
 
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Metadata
Title
Behavior Clustering and Explicitation for the Study of Agents’ Credibility: Application to a Virtual Driver Simulation
Authors
Kévin Darty
Julien Saunier
Nicolas Sabouret
Copyright Year
2015
Book
Agents and Artificial Intelligence

Print ISBN: 978-3-319-25209-4

Electronic ISBN: 978-3-319-25210-0

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-25210-0_6

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