Emotional agents for collaborative e-learning

Revised: September 30th, 2007 ABSTRACT. In this paper, we discuss the social intelligence that renders affective behaviours of intelligent agents, and its application to a collaborative learning system. We argue that socially appropriate affective behaviours would provide a new dimension for collaborative learning systems. The description of a system to recognize the six universal facial expressions (happiness, sadness, anger, fear, surprise, and disgust) using an agent-based approach is presented. Then, we describe how emotions can efficiently and effectively be visualized in Collaborative Virtual Environments, or CVEs, with an animated virtual head (Emotional Embodied Conversational Agent, or EECA) that is designed to express and act in response to the “universal facial expressions”. The objective of the paper is to present the emotional framework EMASPEL, that is Emotional Multi-Agents System for Peer to peer E-Learning, based on the Multi-Agents Architecture approach.