Ontology engineering and modelling for learning activity in a multiagent system

EHIMWENMA, Kennedy, BEER, Martin and CROWTHER, Paul (2014). Ontology engineering and modelling for learning activity in a multiagent system. In: SIMS '14 Proceedings of the 2014 First International Conference on Systems Informatics, Modelling and Simulation. Washington, DC, IEEE Computer Society, 117-181.

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Official URL: doi:10.1109/SIMS.2014.35


Prior and personalised learning is one area in cognitive learning that can be engineered on the platform of agent based intelligent systems. The requirement for inviting prior learning into a new learning context is the concept relationships between previous learning and the desired learning. In this paper this relationship has been established using ontology and mutliagent system in orchestrating a more personalised learning. This paper thus, present the use of Protege in the design of structured learning concepts in the domain of Computer Architecture. In this knowledge representation, attributes or properties are specified for classes, subclasses and individual members along with their constraints using Universal and Existential Restrictions. To the individuals, universal resource locator (URL) data values of the type string are assigned using the Data Property. And this process which has evolved in the development of a multiagent system for assessing prior learning before the take-off of new learning using Jason AgentSpeak language.

Item Type: Book Section
Additional Information: Published paper from the conference : 1st International Conference on Systems Informatics, Modelling and Simulation, SIMS2014, 29 April - 1 May 2014, Sheffield, UK
Research Institute, Centre or Group: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Departments: Faculty of Science, Technology and Arts > Department of Computing
Depositing User: Martin Beer
Date Deposited: 12 Feb 2015 13:32
Last Modified: 13 Jun 2017 13:27
URI: http://shura.shu.ac.uk/id/eprint/9308

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