Agents Control for Intelligent E-Learning Systems

The control and arbitration problem has been an important issue for multi-agent systems. Intelligent e-learning systems (ILS) based nowadays on agents and cognitive modeling to enhance their functionality, present specific features for handling arbitration or control. The paper analyses several control mechanisms directly related to ILS operation and performance, based on certain stimuli received by agents. Practical results are given referred to the operation of NEOCAMPUS2, a specific platform for ILS development

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