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Descripción
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| This article proposes a MAS architecture for network diagnosis under uncertainty. Network diagnosis is divided into two inference processes: hypothesis generation and hypothesis con?rmation. The ?rst process is distributed among several agents based on a Multiply Sectioned Bayesian Network (MSBN), while the second one is carried out by agents using semantic reasoning. A diagnosis ontology has been de?ned in order to combine both inference processes. To drive the deliberation process, dynamic data about the in?uence of observable variables (data) are taken during diagnosis process. In order to achieve quick and reliable diagnoses, this in?uence is used to choose the best action to perform. This approach has been evaluated in a P2P video streaming scenario. Computational and time improvements are highlight as conclusions. | |
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Internacional
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Si |
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Nombre congreso
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9th European Workshop on Multi-agent Systems (EUMAS 2011) |
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Tipo de participación
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960 |
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Lugar del congreso
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Maastricht, The Netherlands |
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Revisores
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Si |
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ISBN o ISSN
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DOI
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Fecha inicio congreso
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14/11/2011 |
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Fecha fin congreso
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15/11/2011 |
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Desde la página
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11 |
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Hasta la página
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25 |
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Título de las actas
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Proceedings of the 9th European Workshop on Multi-agent Systems |