The rise of granular computing

This paper has two purposes. One is to present a critical examination of the rise of granular computing and the other is to suggest a triarchic theory of granular computing. By examining the reasons, justifications, and motivations for the rise of granular computing, we may be able to fully appreciate its scope, goal and potential values. The results enable us to formulate a triarchic theory in the light of research results from many disciplines. The three components of the theory are labeled as the philosophy, the methodology, and the computation. The integration of the three offers a unified view of granular computing as a way of structured thinking, a method of structured problem solving, and a paradigm of structured information processing, focusing on hierarchical granular structures. The triarchic theory is an important effort in synthesizing the various theories and models of granular computing.

[1]  Hung Son Nguyen,et al.  Granular Computing: a Rough Set Approach , 2001, Comput. Intell..

[2]  Yingxu Wang,et al.  The Theoretical Framework of Cognitive Informatics , 2007, Int. J. Cogn. Informatics Nat. Intell..

[3]  Craig A. Knoblock.  Generating abstraction hierarchies - an automated approach to reducing search in planning , 1993, The Kluwer international series in engineering and computer science.

[4]  Yiyu Yao,et al.  Perspectives of granular computing , 2005, 2005 IEEE International Conference on Granular Computing.

[5]  Nancy Stern,et al.  The Rise of Systems Theory: An Ideological Analysis by Robert Lilienfeld (review) , 1979 .

[6]  Andrzej Bargiela,et al.  Toward a Theory of Granular Computing for Human-Centered Information Processing , 2008, IEEE Transactions on Fuzzy Systems.

[7]  Maria Semeniuk-Polkowska,et al.  On Foundations and Applications of the Paradigm of Granular Rough Computing , 2008, Int. J. Cogn. Informatics Nat. Intell..

[8]  Wei-Zhi Wu,et al.  Attribute Granules in Formal Contexts , 2009, RSFDGrC.

[9]  Yiyu Yao,et al.  A multiview approach for intelligent data analysis based on data operators , 2008, Inf. Sci..

[10]  S. Tsumoto,et al.  Rough Set Theory and Granular Computing , 2003 .

[11]  桐山 伸也.  "The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind," Marvin Minsky, Simon & Schuster, 2006(私のすすめるこの一冊,コーヒーブレイク) , 2007 .

[12]  Jiming Liu,et al.  Toward nature-inspired computing , 2006, CACM.

[13]  L. Zadeh,et al.  Data mining, rough sets and granular computing , 2002 .

[14]  R. Kurzweil,et al.  The Singularity Is Near: When Humans Transcend Biology , 2006 .

[15]  Lotfi A. Zadeh,et al.  Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic , 1997, Fuzzy Sets Syst..

[16]  Yiyu Yao,et al.  Granular computing for data mining , 2006, SPIE Defense + Commercial Sensing.

[17]  Lionel Tarassenko,et al.  Cognitive Systems - Information Processing Meets Brain Science , 2005 .

[18]  A. Skowron,et al.  Towards adaptive calculus of granules , 1998 .

[19]  Yiyu Yao,et al.  A Partition Model of Granular Computing , 2004, Trans. Rough Sets.

[20]  Yiyu Yao,et al.  Web Intelligence Meets Brain Informatics , 2006, WImBI.

[21]  Z. Pawlak.  Granularity of knowledge, indiscernibility and rough sets , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[22]  E. László.  The systems view of the world: The natural philosophy of the new developments in the sciences , 1975 .

[23]  Hans P. Moravec.  Mind Children: The Future of Robot and Human Intelligence , 1988 .

[24]  Yiyu Yao,et al.  Granular Computing: basic issues and possible solutions , 2007 .

[25]  Yiyu Yao,et al.  The Art of Granular Computing , 2007, RSEISP.

[26]  Duoqian Miao,et al.  Application of Granular Computing in Knowledge Reduction , 2006, RSKT.

[27]  Lars Skyttner.  General Systems Theory: Ideas and Applications , 2001 .

[28]  Oscar Cullmann,et al.  Unity Through Diversity , 1988 .

[29]  JingTao Yao.  A Ten-year Review of Granular Computing , 2007 .

[30]  S. Pinker.  How the Mind Works , 1999, Philosophy after Darwin.

[31]  John Taylor.  Introduction Brain Science and Information Technology – Do They Add Up? , 2006 .

[32]  Fei-Yue Wang,et al.  Covering Based Granular Computing for Conflict Analysis , 2006, ISI.