Adaptive e-Learning Multi-Agent Systems with Swarm Intelligence
Manuj Darbari and Priya Sahai. Article: Adaptive e-Learning Multi-Agent Systems with Swarm Intelligence. International Journal of Applied Information Systems 7(3):16-20, May 2014. BibTeX
@article{key:article, author = "Manuj Darbari and Priya Sahai", title = "Article: Adaptive e-Learning Multi-Agent Systems with Swarm Intelligence", journal = "International Journal of Applied Information Systems", year = 2014, volume = 7, number = 3, pages = "16-20", month = "May", note = "Published by Foundation of Computer Science, New York, USA" }
Abstract
In this paper we propose a multi-agent approach to the problem of recommending relevant and adequate study material to the learner in E-learning environment. It illustrates swarm intelligence of bee-colony optimization that enables agents to recommend learner most appropriate data content in real –time which stored in the form of case-sets. A flexibility, adaptability and interactiveness is achieved through agents that autonomously and intelligently uses swarm intelligent algorithms to recommend course structure to learners . Secondly we have suggested construction of a cache knowledge base which will be updated by swarm intelligent agents by analysing various parameters such as learners feedbacks, their educational records and other parameters.
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Keywords
E-learning, swarm intelligence , multi-agent system, cache, Baye’s theorem