An evaluation of the COR-E computational model for affective behaviors

The simulation of believable behaviors for virtual agents requires to take human factors such as emotions into account. Most computational models dealing with this issue include emotion categories in their architecture. However, determining categories to use and their influence on behavior is a difficult task. In order to address this challenge, our COR-E model uses an architecture without emotion categories. In this paper, we present an evaluation of this model in the context of a waiting line scenario. We show that COR-E can produce believable emotional behaviors, and test the contributions of the various components and characteristics of its architecture to these positive results.