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.