An Intelligent Multiagent Tutoring System (IMATS) in Artificial Intelligence (AI) is presented in this paper. The authors describe ways of improving the quality of teaching AI through the use of agent technology. An interface agent, an authorization agent, an SQL agent, and a student agent can be integrated into the intelligent learning environment. These agents can guide and assist students as needed, probe their understanding, and promote learning and retention. They also exploit the natural human tendency to respond socially to computing systems. Here a brief historical perspective of intelligent learning environments is discussed and followed by an explanation of the IMATS framework. Next, a detaileddescription of the intelligent tutoring system, IMATS, is given. Then the results of usability evaluation, effectiveness evaluation, and satisfaction level evaluation of the software system are presented. The IMATS framework incorporates an incremental approach to obtain the dynamics of knowledge accumulation in the domain of interest and the learned knowledge content over time.
如有問題歡迎與系統管理員聯繫 
