AMMAS: Ambient Mobile Multi-Agents System: Simulation of the M-Learning

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Shili Mohamed 1,* Moez Chebbi 1 Santosh Kumar Behera 2

1. Institute of Applied Science and Technology of Sousse, Tunisia, IT university teacher at the Higher Institute of Technological Studies (Kairouan, Tunisia)

2. Assistant Professor, Dept. of Education, Sidho-Kanho-Birsha University, Purulia, West Bengal, India

* Corresponding author.


Received: 26 Oct. 2016 / Revised: 19 Nov. 2016 / Accepted: 10 Dec. 2016 / Published: 8 Jan. 2017

Index Terms

Mobile Agent, M-Learning, E-Learning, Adaptability, Context Aware.


Recent years have witnessed the increase of the field of mobile learning, fostered by the continuous development of mobile computing and wireless technology, today the mobile learning presents a fundamental approach to satisfy our daily needs and requirements. Specifically, in this work, we aim to study as model and simulate the ambient mobile system which is based on intelligent agents. The mobile agent is not based on the traditional client server however it is based on the distributed ones. The present article proposes a mobile intelligent agent based architecture for the M-Learning that aims to facilitate the teacher and student acquisition. M-Learning is a new research area which became a principal tool for our education system. So we produced an adapted agent based approach for an efficient flexible.
In our work we proceed as follows: first, we introduce the scope and the genesis of our research, second, we hold out the m-learning is the next generation of e-learning, afterwards, we present our AMMAS (Ambient Mobile Multi-Agents System) model for the M-Learning and an overview of the system implementation, and finally we conclude our work and give some perspectives.

Cite This Paper

Shili Mohamed, Moez Chebbi, Santosh Kumar Behera,"AMMAS: Ambient Mobile Multi-Agents System: Simulation of the M-Learning", International Journal of Modern Education and Computer Science(IJMECS), Vol.9, No.1, pp.36-42, 2017.DOI: 10.5815/ijmecs.2017.01.04


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