Exploiting independence in a decentralised and incremental approach of diagnosis

Alban Grastien 1 Marie-Odile Cordier 2
2 DREAM - Diagnosing, Recommending Actions and Modelling
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : It is well-known that the size of the model is a bottleneck when using model-based approaches to diagnose complex systems. To answer this problem, decentralised/distributed approaches have been proposed. Another problem, which is far less considered, is the size of the diagnosis itself. However, it can be huge enough, especially in the case of on-line monitoring and when dealing with uncertain observations. We define two independence properties (state and transition-independence) and show their relevance to get a tractable representation of diagnosis in the context of both decentralised and incremental approaches. To illustrate the impact of these properties on the diagnosis size, experimental results on a toy example are given.
Type de document :
Communication dans un congrès
IJCAI 07, Jan 2007, Hyderabad, 2007
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https://hal.inria.fr/inria-00110584
Contributeur : Alban Grastien <>
Soumis le : mardi 31 octobre 2006 - 00:59:53
Dernière modification le : mardi 16 janvier 2018 - 15:54:11
Document(s) archivé(s) le : mardi 6 avril 2010 - 21:19:02

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  • HAL Id : inria-00110584, version 1

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Alban Grastien, Marie-Odile Cordier. Exploiting independence in a decentralised and incremental approach of diagnosis. IJCAI 07, Jan 2007, Hyderabad, 2007. 〈inria-00110584〉

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