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The elderly population worldwide has an increasing expectation of well-being and life expectancy. The monitoring of elderly people on an individual basis, in a medical sense, will not be a viable proposition in the future. The infrastructure available is not adequate to meet all expectations and subsequently people will continue to live at home with inadequate care. Prior research has shown an accelerated need for the expansion in the Ambient Intelligence (AmI) domain and to that end we present a novel learning technique for intelligent agents that are embedded in Ambient Intelligent Environments (AIEs). A novel agent that combines an emotion recognition system with a fuzzy logic based learning and adaptation technique provides for an automated self-learning system that constantly adapts to individual requirements. This agent, entitled Health Adaptive Emotion Fuzzy Agent (HAOEFA), has the ability to model and learn the user behaviour in order to control the environment on their behalf with respect to his/her emotional preferences. In addition, the agent incorporates temporal adaption in order to facilitate changing behaviour and preferences within the environment. The results show that such architecture can both provide monitoring and ambient environmental control features such that users with limited physical or cognitive functions can have their well-being advanced with limited external resources.