An Intelligent Fuzzy Agent Approach for Realising Ambient Intelligence in Intelligent Inhabited Environments

In this paper we describe a novel life long learning approach for intelligent agents that are embedded in intelligent environments. The agents aim to realise the vision of Ambient Intelligence in Intelligent Inhabited Environments (IIE) by providing 'ubiquitous computing intelligence in the environment supporting the activities of the user. An unsupervised, data-driven, fuzzy, technique is proposed for extracting fuzzy membership functions and rules that represent the user's particularised behaviours in the environment. The user's learnt behaviours can then be adapted online in a life long mode to satisfy the different user and system objectives. We have performed unique experiments in which the intelligent agent has learnt and adapted to the user's behaviour, during a stay of five consecutive days in the intelligent Dormitory (iDorm) which is a real ubiquitous computing environment test bed. Both offline and online experimental results are presented comparing the performance of our technique with other approaches. The results show that our proposed system has outperformed the other systems while operating online in a life long mode to realise the ambient intelligence vision.

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