Multi-agent architecture for intelligent E-learning

Arriaga, Fernando de; Alami, Majida El; Arriaga, A.

doi:10.1109/icecs.2003.1301735

Cited by 5 publications

(3 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Diverse software programs or basic software platforms have been developed to ease the task of designing and implementing intelligent agents, such as JADE [102], AgentSpeak [103], ProMAS [104] and NEOCAMPUS [105]. In our case, the choice has been clear because of the greater flexibility supplied by NEOCAMPUS.…”

Section: Functionalitymentioning

confidence: 99%

DIAUTIS: A Fuzzy and Affective Multi-agent Platform for the Diagnosis of Autism

Alami

Tahiri

Arriaga

2017

BJAST

View full text Add to dashboard Cite

Autism is a disease that appears in the first stage of life and produces significant imbalances in the behaviour of people affected by this disease. According to existing data, autism is growing at an alarming rate. Its early diagnosis is important to be able to administer to the patient the aids it refers to, especially those related to learning. DIAUTIS is a platform that aims to help the clinical team, doctors, parents, tutors and schools in the diagnosis of this disease. Its ability to cognitive, fuzzy, and affective computing, with the capability to learn from experience, endows the multi-agent system many possibilities. One of them is to present collections of tests of various categories, evaluate the results of the child, and present a final model of his/her condition and the severity of the disease.The tests performed show that DIAUTIS is ready to initiate a long series of diagnostic tests with reliability and efficiency. Original Research ArticleEl Alami et al.; BJAST, 21(4): 1-28, 2017; Article no.BJAST.33716 2

show abstract

Section: Functionalitymentioning

confidence: 99%

DIAUTIS: A Fuzzy and Affective Multi-agent Platform for the Diagnosis of Autism

Alami

Tahiri

Arriaga

2017

BJAST

View full text Add to dashboard Cite

show abstract

“…The flexibility and robustness obtained from multi-agent systems makes them suitable to be used in Web environments [22]. Multi-agent systems could simulate a specialist when making pedagogical tasks [20]. Based on the above considerations, our architecture will be based on multi agent methodology.…”

Section: Multi-agent Technologymentioning

confidence: 99%

A multi-agent architecture for adaptive E-learning systems using a blackboard agent

Hammami

Mathkour

Al-Mosallam

2009

2009 2nd IEEE International Conference on Computer Science and Information Technology

View full text Add to dashboard Cite

show abstract

“…It is out of the scope of this paper to review the broad field of intelligent e-learning systems, but closer to this paper, the modular agent architecture used in this work [23] and some of its applications [24], [25] have to be cited. The specific knowledge needed by the agents to execute the assigned task is divided in three layers according to the response time of the execution of the corresponding agent action; so, the reactive layer includes knowledge needed for rapid and vital agent responses, the tactic layer includes the knowledge for executing procedures and actions not so rapid, and the strategic layer supports the knowledge for long time decisions, long range planning and cooperation procedures.…”

Section: Intelligent E-learning Systems: Neocampusmentioning

confidence: 99%

Intelligent E-learning Systems and the Transfer of Novices into Experts

Alami¹,

Arriaga²

2013

IJCA

View full text Add to dashboard Cite

In our knowledge society learning is a very important and broad topic that includes several unsolved questions. Among them the transfer of novices into experts remains elusive. The paper shows that the cognitive elements and mental models needed for the expert execution of a task or skill can be used in cooperation with suitable exercises and intelligent elearning systems to obtain a faster and more robust transfer of novices into experts. The paper also discusses the role of mental models and how can they be obtained from human experts. It also includes a state-space methodology to know the obtained place for the apprentice within the transfer process and how to move him optimally towards the final or expert state. A particular example for decision making by using an intelligent e-learning system simulating a private Medical Centre is included and the obtained results for more than five years are assessed.

show abstract

Multi-agent architecture for intelligent E-learning

Cited by 5 publications

References 2 publications

DIAUTIS: A Fuzzy and Affective Multi-agent Platform for the Diagnosis of Autism

DIAUTIS: A Fuzzy and Affective Multi-agent Platform for the Diagnosis of Autism

A multi-agent architecture for adaptive E-learning systems using a blackboard agent

Intelligent E-learning Systems and the Transfer of Novices into Experts

Contact Info

Product

Resources

About