Agents Behavior Semi-automatic Analysis through Their Comparison to Human Behavior Clustering

This paper presents a generic method to evaluate virtual agents that aim at reproducing humans behaviors in an immersive virtual environment. We first use automated clustering of simulation logs to extract humans behaviors. We then propose an aggregation of the agents logs into those clusters to analyze the credibility of agents behaviors in terms of capacities, lacks, and errors by comparing them to humans ones. We complete this analysis with a subjective evaluation based on a questionnaire filled by human annotators to draw categories of users, making their behaviors explicit. We illustrate this method in the context of immersive driving simulation.

[1]  Philippe Caillou,et al.  SimAnalyzer: automated description of groups dynamics in agent-based simulations , 2012, AAMAS.

[2]  S Stradling,et al.  Errors and violations on the roads: a real distinction? , 1990, Ergonomics.

[3]  Philip Chan,et al.  Toward accurate dynamic time warping in linear time and space , 2007, Intell. Data Anal..

[4]  Ning Wang,et al.  Creating Rapport with Virtual Agents , 2007, IVA.

[5]  D. de Waard,et al.  Handbook of driving simulation for engineering, medicine and psychology , 2011 .

[6]  James C. Lester,et al.  The persona effect: affective impact of animated pedagogical agents , 1997, CHI.

[7]  Pramod K. Varshney,et al.  Modern Approaches in Applied Intelligence - 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Syracuse, NY, USA, June 28 - July 1, 2011, Proceedings, Part I , 2011, IEA/AIE.

[8]  Jean-Michel Auberlet,et al.  Behavioral Road Traffic Simulation with ARCHISIM , 2000 .

[9]  Stacy Marsella,et al.  Evaluating a Computational Model of Emotion , 2005, Autonomous Agents and Multi-Agent Systems.

[10]  Gary Fontaine,et al.  The Experience of a Sense of Presence in Intercultural and International Encounters , 1992, Presence: Teleoperators & Virtual Environments.

[11]  Catherine Pelachaud,et al.  Modelling multimodal expression of emotion in a virtual agent , 2009, Philosophical Transactions of the Royal Society B: Biological Sciences.

[12]  Michel C. A. Klein,et al.  Agent-Based Analysis of Patterns in Crowd Behaviour Involving Contagion of Mental States , 2011, IEA/AIE.

[13]  Mohamed Chetouani,et al.  Interpersonal Synchrony: A Survey of Evaluation Methods across Disciplines , 2012, IEEE Transactions on Affective Computing.

[14]  Etienne de Sevin,et al.  An evaluation of the COR-E computational model for affective behaviors , 2013, AAMAS.

[15]  Sriram Subramanian,et al.  Talking about tactile experiences , 2013, CHI.

[16]  T. Caliński,et al.  A dendrite method for cluster analysis , 1974 .

[17]  Nicolas Sabouret,et al.  A Method for Semi-automatic Explicitation of Agent's Behavior - Application to the Study of an Immersive Driving Simulator , 2014, ICAART.