Hybrid Computational Intelligence for Ambient Intelligent Environments

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Abstract

This paper describes an agent-based ambient intelligence architecture able to deliver personalized services on the basis of physical and emotional user status captured from a set of biometric features. Abstract representation and management is achieved thanks to two markup languages, H2ML and FML, able to model behavioral as well as fuzzy control activities and to exploit distribution and concurrent computation in order to gain real-time performances.