Adaptivity implementation based on multi-agent technology

An adaptive user system can be helpful to improve the quality of human-computer interaction. Because of the one-size-fits-all user interface, most people in Web-based learning have to face lack of support on adaptive learning. Agents are autonomous and computational entities that can be viewed as perceiving and acting upon their environment. We make use of multi-agent system (MAS) technology in artificial intelligence to implement adaptivity to improve the users´ study in quality dynamically. We start our work with a 4-key-component interaction model for adaptivity to construct special user models. On the basis of them an adaptive learning system is designed and implemented using MAS technology. Following that the architecture and working process of this system are presented. And then we introduce how to get learning resource adaptive to users; examples are also given to evaluate the adaptiveness.