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This paper presents an enhanced type-2 fuzzy logic based agent that can be embedded in multi-occupant Ambient Intelligent Environments (AIEs). The agent utilizes the power of type-2 fuzzy logic in modeling various types of uncertainties (especially inter-user uncertainties) and the agent non-intrusively learns the collective behavior of the occupants from their individual type-1 profiles. Knowledge about the users' behavior and preferences is encoded in the form of type-2 rules and membership functions. The agent then uses the captured behavior to control the environment on behalf of the users and adapt in the short term as well as to long term changes in the environment or the users' habits. Multiple real world experiments were carried out in the Intelligent Classroom (iClass) (which is based in the Ambient Intelligence Centre “AMIC” at the German University in Cairo (GUC)), to evaluate the performance of the agent.

An Adaptive Type-2 Fuzzy Logic Based Agent for Multi-Occupant Ambient Intelligent Environments.