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.