527 research outputs found

    Improving interoperability among learning objects using FIPA agent communication framework

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    The reusability of learning material is based on three main features: modularity, discoverability and interoperability. Several researchers on Intelligent Learning Environments have proposed the use of architectures based on agent societies. Learning systems based on Multi-Agent architectures support the development of more interactive and adaptable systems and the Learning Objects approach gives reusability. We proposed an approach where learning objects are built based on agent architectures. This paper discusses how the Intelligent Learning Objects approach can be used to improve the interoperability between learning objects and pedagogical agents.Applications in Artificial Intelligence - AgentsRed de Universidades con Carreras en InformĂĄtica (RedUNCI

    Improving interoperability among learning objects using FIPA agent communication framework

    Get PDF
    The reusability of learning material is based on three main features: modularity, discoverability and interoperability. Several researchers on Intelligent Learning Environments have proposed the use of architectures based on agent societies. Learning systems based on Multi-Agent architectures support the development of more interactive and adaptable systems and the Learning Objects approach gives reusability. We proposed an approach where learning objects are built based on agent architectures. This paper discusses how the Intelligent Learning Objects approach can be used to improve the interoperability between learning objects and pedagogical agents.Applications in Artificial Intelligence - AgentsRed de Universidades con Carreras en InformĂĄtica (RedUNCI

    Towards engineering ontologies for cognitive profiling of agents on the semantic web

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    Research shows that most agent-based collaborations suffer from lack of flexibility. This is due to the fact that most agent-based applications assume pre-defined knowledge of agents’ capabilities and/or neglect basic cognitive and interactional requirements in multi-agent collaboration. The highlight of this paper is that it brings cognitive models (inspired from cognitive sciences and HCI) proposing architectural and knowledge-based requirements for agents to structure ontological models for cognitive profiling in order to increase cognitive awareness between themselves, which in turn promotes flexibility, reusability and predictability of agent behavior; thus contributing towards minimizing cognitive overload incurred on humans. The semantic web is used as an action mediating space, where shared knowledge base in the form of ontological models provides affordances for improving cognitive awareness

    Supporting internet-scale multi-agent systems

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    The Use of Multi-Agents\u27 Systems in e-Learning Platforms

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    Ontology-based services for agents interoperability

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    Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2006. Faculdade de Engenharia. Universidade do Port
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