Distributed Classification: Architecture and Cooperation Protocol in a Multi-agent System for E-Health

We propose an agent-based architecture to build classifications from evolutionary and distributed data. In the process, each agent builds a partial classification based on its data and a complete classification is then constructed from the partial ones by comparing them. Agents can collaborate by employing a restricted cooperation protocol. We present an application in the e-health domain, where global behavior patterns are built from activity or physiological data related to elderly people monitored at home by a variety of sensors. A step-by-step example illustrates our proposition.

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