Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12540/168
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dc.contributor.authorEhimwenma, Kennedy E.en_US
dc.contributor.authorKrishnamoorthy, Sujathaen_US
dc.date.accessioned2020-09-17T11:46:48Z-
dc.date.available2020-09-17T11:46:48Z-
dc.date.issued2020-
dc.identifier.citationEhimwenma, K. E., & Krishnamoorthy S. (2020). Design and analysis of a multi-agent e-learning system using prometheus design tool. IAES International Journal of Artificial Intelligence (IJ-AI), 9(4), 31-45.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12540/168-
dc.description.abstractAgent unified modeling languages (AUML) are agent-oriented approaches that supports the specification, design, visualization and documentation of an agent-based system. This paper presents the use of Prometheus AUML approach for the modeling of a Pre-assessment System of five interactive agents. The Pre-assessment System, as previously reported, is a multi-agent based e-learning system that is developed to support the assessment of prior learning skills in students so as to classify their skills and make recommendation for their learning. This paper discusses the detailed design approach of the system in a step-by-step manner; and domain knowledge abstraction and organization in the system. In addition, the analysis of the data collated and models of prediction for future pre-assessment results are also presented.en_US
dc.format.extent15 pagesen_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoengen_US
dc.publisherUAD Institute of Scientific Publication and Press (LPPI)en_US
dc.relation.ispartofIAES International Journal of Artificial Intelligence (IJ-AI)en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/-
dc.subject.lcshEducationen_US
dc.subject.lcshFirst-order Logicen_US
dc.subject.lcshRequirements Engineeringen_US
dc.titleDesign and analysis of a multi-agent e-learning system using prometheus design toolen_US
dc.typeArticleen_US
dc.rights.licenseAttribution-NonCommercial 4.0 International (CC BY-NC 4.0)en_US
dc.identifier.doi10.11591/ijai.v9.i4.pp%25p-
dc.subject.keywordsAgent Methodologyen_US
dc.subject.keywordsPre-assessment Classificationen_US
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