Proposition of an Intelligent Multi-Agent System for Learning


  • Gazissou Balama Department of Mathematics and Computer Science, Faculty of Sciences, University of Ngaoundere, Cameroon
  • Dayang Paul Department of Mathematics and Computer Science, Faculty of Sciences, University of Ngaoundere, Cameroon.
  • Kolyang . Department of Computer Science, High Teacher Training College, University of Maroua, Cameroon


Intelligent System, Learning, MASIL, Multi-Agent System


In this paper, an intelligent Multi-Agent System (MAS) for learning, that we have called MASIL, is proposed. MASIL’s architecture is based on the hybrid client-server, multi-agent and Machine Learning model. After creating the different agents of the system and defining the different roles, we formed groups of agents according to our architecture to make our system more efficient. After this step, we had to find an operating mechanism to make MASIL as efficient as possible. To try to solve this problem we used the approach of the Operating System kernel and made some connections with the MASIL agents. To make MASIL smarter, we built machine learning models for certain of our agents. The evaluation of the system has shown that MASIL is being formed as lessons are being learned and is becoming increasingly intelligent


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