A Computing with Words Framework for Ambient Intelligence

One of the challenges for the fast advancing ambient intelligence vision is to maintain the perception of the future home being a safe place where the inhabitants relax, enjoy and feel comfortable. In a home environment, the role of technology is approached skeptically, hence, there is a need to provide high-level communication between the users and the intelligent space so that the users get accustomed to what technology has to offer. In this paper, we introduce a Computing with Words (CWWs) framework which provides human-like reasoning via abstraction and high-level description of thoughts, feelings, etc. This framework can be considered as an exocortex as it aids the human thinking outside the bio-brain. The CWWs paradigm aims to establish high level home-human communication, which is necessary for people to perceive the technology as a cooperative guide and an improvement on their life styles.

[1]  G. A. Miller.  THE PSYCHOLOGICAL REVIEW THE MAGICAL NUMBER SEVEN, PLUS OR MINUS TWO: SOME LIMITS ON OUR CAPACITY FOR PROCESSING INFORMATION 1 , 1956 .

[2]  Hani Hagras,et al.  Fuzzy Composite Concepts based on human reasoning , 2010, 2010 IEEE International Conference on Information Reuse & Integration.

[3]  Jerry M. Mendel,et al.  A comparative study of ranking methods, similarity measures and uncertainty measures for interval type-2 fuzzy sets , 2009, Inf. Sci..

[4]  Hani Hagras,et al.  Towards a linear general type-2 fuzzy logic based approach for computing with words , 2013, Soft Comput..

[5]  Hani Hagras,et al.  An experience based linear general type-2 fuzzy logic approach for Computing With Words , 2013, 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[6]  R. A. M. O N L O P E Z D E M A N T A R A S,et al.  Retrieval, reuse, revision and retention in case-based reasoning , 2006 .

[7]  M. Katsevman,et al.  Exploring the Exocortex: An Approach to Optimizing Human Productivity , 2008 .

[8]  Michael Friedewald,et al.  Perspectives of ambient intelligence in the home environment , 2005 .

[9]  Hani Hagras,et al.  Towards a general type-2 fuzzy logic approach for Computing With Words using linear adjectives , 2012, 2012 IEEE International Conference on Fuzzy Systems.

[10]  John Field,et al.  Psycholinguistics: A Resource Book for Students , 2003 .

[11]  Ana Gabriela Maguitman,et al.  Cases, Context, and Comfort: Opportunities for Case-Based Reasoning in Smart Homes , 2006, Designing Smart Homes.

[12]  Juan Carlos Augusto,et al.  Learning patterns in ambient intelligence environments: a survey , 2010, Artificial Intelligence Review.

[13]  R. Michalski.  Understanding the Nature of Learning: Issues and Research Directions , 1985 .

[14]  Leslie G. Ungerleider,et al.  The neural systems that mediate human perceptual decision making , 2008, Nature Reviews Neuroscience.

[15]  Hani Hagras,et al.  Toward General Type-2 Fuzzy Logic Systems Based on zSlices , 2010, IEEE Transactions on Fuzzy Systems.

[16]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[17]  Henri Prade,et al.  Fuzzy set modelling in case-based reasoning , 1998, Int. J. Intell. Syst..

[18]  J. Aitchison.  Words in the Mind: An Introduction to the Mental Lexicon , 1987 .

[19]  Gian Luca Foresti,et al.  Ambient Intelligence: A New Multidisciplinary Paradigm , 2005 .

[20]  Lotfi A. Zadeh,et al.  Fuzzy logic = computing with words , 1996, IEEE Trans. Fuzzy Syst..

[21]  Sergio Guadarrama,et al.  What about fuzzy logic's linguistic soundness? , 2005, Fuzzy Sets Syst..