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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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Contributor : Catherine Garbay Connect in order to contact the contributor
Submitted on : Monday, October 15, 2012 - 7:42:29 PM
Last modification on : Wednesday, July 6, 2022 - 4:24:51 AM
Long-term archiving on: : Wednesday, January 16, 2013 - 3:05:11 AM


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Benoît Vettier, Laure Amate, Catherine Garbay. A Multi-Hypothesis Monitoring Architecture: Application to Ambulatory Physiology. Starting AI Researchers' Symposium, Aug 2012, Montpellier, France. pp.348-359, ⟨10.3233/978-1-61499-096-3-348⟩. ⟨hal-00740706⟩



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