Three Perspectives of Granular Computing

As an emerging field of study, granular computing has received much attention. Many models, frameworks, methods and techniques have been proposed and studied. It is perhaps the time to seek for a general and unified view so that fundamental issues can be examined and clarified. This paper examines granular computing from three perspectives. By viewing granular computing as a way of structured thinking, we focus on its philosophical foundations in modeling human perception of the reality. By viewing granular computing as a method of structured problem solving, we examine its theoretical and methodological foundations in solving a wide range of realworld problems. By viewing granular computing as a paradigm of information processing, we turn our attention to its more concrete techniques. The three perspectives together offer a holistic view of granular computing.

[1]  John F. Sowa,et al.  Conceptual Structures: Information Processing in Mind and Machine , 1983 .

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

[3]  Yiyu Yao,et al.  Information granulation and rough set approximation , 2001, Int. J. Intell. Syst..

[4]  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..

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

[6]  Witold Pedrycz,et al.  Granular Computing - The Emerging Paradigm , 2007 .

[7]  Andrzej Bargiela,et al.  The roots of granular computing , 2006, 2006 IEEE International Conference on Granular Computing.

[8]  Yiyu Yao,et al.  Granular Computing Based on Rough Sets, Quotient Space Theory, and Belief Functions , 2003, ISMIS.

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

[10]  Shushma Patel,et al.  A layered reference model of the brain (LRMB) , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[11]  Joan I. Heller,et al.  Knowledge structure and problem solving in physics , 1982 .

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

[13]  H. Simon,et al.  The Organization of Complex Systems , 1977 .

[14]  Y. Yao.  Granular Computing : basic issues and possible solutions , 2000 .

[15]  T. Allen,et al.  Hierarchy Theory: A Vision, Vocabulary, and Epistemology , 1996 .

[16]  Potential Applications of Granular Computing in Knowledge Discovery and Data Mining , 1999 .

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

[18]  Jon F. Hueras,et al.  PASCAL with style : programming proverbs , 1979 .

[19]  Lotfi A. Zadeh,et al.  Some reflections on soft computing, granular computing and their roles in the conception, design and utilization of information/intelligent systems , 1998, Soft Comput..

[20]  Yiyu Yao,et al.  Granular computing using information tables , 2002 .

[21]  Yiyu Yao,et al.  On modeling data mining with granular computing , 2001, 25th Annual International Computer Software and Applications Conference. COMPSAC 2001.

[22]  Yiyu Yao,et al.  Granular Computing , 2008 .

[23]  Bo Zhang,et al.  Theory and Applications of Problem Solving , 1992 .

[24]  Bo Zhang,et al.  The Quotient Space Theory of Problem Solving , 2003, Fundam. Informaticae.

[25]  Yiyu Yao,et al.  A Granular Computing Approach to Machine Learning , 2002, FSKD.

[26]  Witold Pedrycz,et al.  Granular computing: an introduction , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[27]  Howard Hunt Pattee,et al.  Hierarchy Theory: The Challenge of Complex Systems , 1973 .

[28]  David Marr,et al.  VISION A Computational Investigation into the Human Representation and Processing of Visual Information , 2009 .

[29]  S. Chipman.  The Remembered Present: A Biological Theory of Consciousness , 1990, Journal of Cognitive Neuroscience.

[30]  Y. Yao.  Granular Computing using Neighborhood Systems , 1999 .

[31]  Yiyu Yao,et al.  Induction of Classification Rules by Granular Computing , 2002, Rough Sets and Current Trends in Computing.