Emotional Multi-Agents System for Peer to peer E-Learning (EMASPEL)

The extraction and recognition of facial expression has been the topic of various researches subject to enable smooth interaction between computer and their users. In this way, computers in the future will be able to offer advice in response to the mood of the users. Humans tend to attribute human qualities to computers. It is expected that people, when using their natural communicational skills, can perform cognitive tasks with computers in a more enjoyable and effective way. For these reasons human-like embodied conversational agents (ECAs) as components of user interfaces have received a lot of attention. In this article, we propose a collective and collaborating e-learning system on the peer to peer network, using the PECS model (Physics, Emotion, Cognition, and Social status) integrated on the Emotional Embodied Conversational Agent (EECA). In order to handle difficulties of learner, to guarantee a more available support at distance and to carry over relevant support due to the learner's emotional state. We describe an affective dialogs with an EECA. We present an update of Emotional Markup Language (EML). Key-Words: facial expression, e-learning, EECA, PECS, EML