A type-2 fuzzy embedded agent to realise ambient intelligence in ubiquitous computing environments

  • Authors:

  • Faiyaz Doctor;Hani Hagras;Victor Callaghan

  • Affiliations:

  • Department of Computer Science, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, United Kingdom;Department of Computer Science, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, United Kingdom;Department of Computer Science, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, United Kingdom

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2005

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Abstract

In this paper, we present a novel approach for realising the vision of ambient intelligence in ubiquitous computing environments (UCEs). This approach is based on embedding intelligent agents in UCEs. These agents use type-2 fuzzy systems which are able to handle the different sources of uncertainty and imprecision in UCEs to give a good response. We have developed a novel system for learning and adapting the type-2 fuzzy agents so that they can realise the vision of ambient intelligence by providing a seamless, unobtrusive, adaptive and responsive intelligence in the environment that supports the activities of the user. The user's behaviours and preferences for controlling the UCE are learnt online in a non-intrusive and life long learning mode 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 will show how our type-2 agents can deal with the uncertainty and imprecision present in UCEs to give a very good response that outperforms the type-1 fuzzy agents while using smaller rule bases.