The Design and Development of Exceptional Representation Based on Domain Ontology and Multi-agent Systems for E-Learning Purposes

2010 ◽  
Author(s):  
Al-Samarrie Hosam ◽  
Merza Abbas ◽  
Irfan Naufal
Keyword(s):  
Domain Ontology ◽  
Multi Agent Systems ◽  
Design And Development ◽  
Agent Systems ◽  
E Learning ◽  
Multi Agent

scholarly journals Cloud e-Learning: A New Challenge for Multi-Agent Systems

2014 ◽  
pp. 277-287 ◽  
Author(s):  
Krenare Pireva ◽  
Petros Kefalas ◽  
Dimitris Dranidis ◽  
Thanos Hatziapostolou ◽  
Anthony Cowling
Keyword(s):  
Multi Agent Systems ◽  
Agent Systems ◽  
E Learning ◽  
Multi Agent

scholarly journals Adaptive Interaction Multi-agent Systems in E-learning/E-teaching on the Web

2003 ◽  
pp. 144-153 ◽  
Author(s):  
Antonio Fernández-Caballero ◽  
Victor López-Jaquero ◽  
Francisco Montero ◽  
Pascual González
Keyword(s):  
Multi Agent Systems ◽  
Agent Systems ◽  
E Learning ◽  
Multi Agent ◽  
Adaptive Interaction ◽  
The Web

Intelligent Clouds

2012 ◽  
pp. 254-279 ◽  
Author(s):  
Mauricio Paletta
Keyword(s):  
Multi Agent Systems ◽  
Cloud Systems ◽  
Agent Systems ◽  
E Learning ◽  
Multi Agent ◽  
Collaboration And Communication

This chapter describes the similarity of intelligent clouds and multi-agent systems. It also explains why intelligent clouds are useful and important. It gives detailed descriptions on how to incorporate intelligent abilities such as learning, negotiation, collaboration, and communication to cloud systems by using IAs. It also details the application of intelligent clouds in e-learning.

scholarly journals MAPSS: An Intelligent Architecture for the Pedagogical Support

2019 ◽  
Vol 14 (14) ◽  
pp. 19
Author(s):  
Najoua Hrich ◽  
Mohamed Lazaar ◽  
Mohamed Khaldi
Keyword(s):  
Artificial Intelligence ◽  
Learning Environments ◽  
Theoretical Foundation ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
E Learning ◽  
Multi Agent ◽  
Learning Platforms ◽  
The Subject ◽  
Competency Evaluation

The multi-agent systems (MAS) are a part of artificial intelligence (AI), they have emerged today in the development of major e-learning platforms. Their integration has given new impetus to learning environments by the possibility of integrating new parameters (psychological, pedagogical, ergonomic…) favoring a better adaptation to the learner. In addition, the multiagent approach offers the possibility to design flexible solutions based on a set of agents which are in continuous communication to accomplish the tasks entrusted to them. In this paper, we propose a model of pedagogical support based on a coupling of ontology and multi-agent systems for a synergy of their forces and the important contribution they can make to improve the learning-teaching process. Previous work has been the subject of theoretical foundation related to competency evaluation, and development of an ontology and an algorithm for evaluating competency. As a continuity, we present the design of Multiagent Pedagogical Support System (MaPSS) and the different scenarios of its utilization.

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