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Computing and storing probabilities is a hard problem as soon as one has to deal with complex distributions over multiples random variables. The problem of efficient representation of probability distributions is central in term of computational efficiency in the field of probabilistic reasoning. The main problem arises when dealing with joint probability(More)
This paper presents the TIISSAD project and its main results. It is related to a telemedicine system type, remote monitoring or follow-up systems. Patients with chronic diseases or elderly (or handicapped) people are the main target for such systems and we aim at preventing accidents or aggravation of the health status of the concerned patients. After an(More)
– A formal framework is proposed for deÞning data fusion processes. Particularly the notion of qualiÞed gain is proposed : gain related to representation, completeness , accuracy and certainty. These notions are applied to a medical monitoring and diagnosis problem where a dynamic Bayesian network is used to modelize time series of observations and evolving(More)
— Telemedicine is the delivery of health-care services, where distance is a critical factor. The use of smart agent and artificial intelligence techniques to enhance such services is proposed through a description of the needs and goals of a smart agent based telemedicine system. A real-world example is presented and the use of dynamic bayesian networks(More)
Cognition and Reasoning with uncertain and partial knowledge is probably the biggest challenge for autonomous mobile robotics. Previous robotics systems based on a purely logical or geometrical paradigm are limited in their ability to deal with partial or uncertain knowledge, adaptation to new environments and noisy sensors. Representing knowledge as a(More)
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