A type-2 fuzzy embedded agent for ubiquitous computing environments

We describe a novel system for learning and adapting type-2 fuzzy controllers for intelligent agents that are embedded in ubiquitous computing environments (UCEs). Our type-2 agents operate non intrusively in an online life long learning manner to learn the user behaviour so as to control the UCE on the user's behalf. We have performed unique experiments in which the type-2 intelligent agent has learnt and adapted online to the user's behaviour during a stay of five days in the intelligent dormitory (iDorm) which is a real UCE test bed. We show how our type-2 agent deals with the uncertainty and imprecision present in UCEs to give a very good performance that outperform the type-1 fuzzy agents while using a smaller number of rules.

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