Individual-Centered E-Learning Based on Artificial Psychology

Nowadays customer preference has aroused concerns in customer satisfaction researches of e-learning, but specifications of user psychology can not been stated clearly in existing tools. This paper describes an individual-centered e-learning tool taking into account the full spectrum of Web mining techniques and activities, presents a multi-agents architecture based on artificial psychology techniques, which will make the e-learning process both adaptable and dynamic, and hence up-to-date. Knowledge base techniques are used to support the adaptation of agents´ cycle, and artificial psychology techniques and beliefs techniques are combined to manage preference and experimental knowledge and to realize more effective and more precise knowledge management.