A Multi-Hypothesis Monitoring Architecture: Application to Ambulatory Physiology

Abstract : In this paper, we propose a normative Multi-Agent System to handle uncertainty in a monitoring application. It is based on the assertion that no single most-likely situation should be considered, thus requiring the management of multiple concurrent hypotheses. A decision is then made by comparing these hypothesized situations to requirements and expectations, thus detecting potential problems. This system uses a large knowledge base of interconnected situation models on several levels of abstraction. It is centered around the need to constantly reconsider which hypotheses should be evaluated, with regards to both the current data from the sensors and wider requirements in terms of efficiency and specific focus from an expected scenario. We propose both a generic concept, and a more specific system for human health monitoring, using ambulatory physiological sensors.
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Communication dans un congrès
Kristian Kersting, Marc Toussaint. Starting AI Researchers' Symposium, Aug 2012, Montpellier, France. IOS Press, 241, pp.348-359, 2012, <10.3233/978-1-61499-096-3-348>
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Contributeur : Catherine Garbay <>
Soumis le : lundi 15 octobre 2012 - 19:42:29
Dernière modification le : mardi 28 octobre 2014 - 18:34:58
Document(s) archivé(s) le : mercredi 16 janvier 2013 - 03:05:11

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Benoît Vettier, Laure Amate, Catherine Garbay. A Multi-Hypothesis Monitoring Architecture: Application to Ambulatory Physiology. Kristian Kersting, Marc Toussaint. Starting AI Researchers' Symposium, Aug 2012, Montpellier, France. IOS Press, 241, pp.348-359, 2012, <10.3233/978-1-61499-096-3-348>. <hal-00740706>

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