On Foundations and Applications of the Paradigm of Granular Rough Computing

Granular computing, initiated by Lotfi A. Zadeh, has acquired wide popularity as a tool for approximate reasoning, fusion of knowledge, cognitive computing. The need for formal methods of granulation, and means for computing with granules, has been addressed in this work by applying methods of rough mereology. Rough mereology is an extension of mereology taking as the primitive notion the notion of a part to a degree. Granules are formed as classes of objects which are a part to a given degree of a given object. In addition to an exposition of this mechanism of granulation, we point also to some applications like granular logics for approximate reasoning and classifiers built from granulated data sets.

[1]  Lech Polkowski,et al.  On Rough Set Logics Based on Similarity Relations , 2005, Fundam. Informaticae.

[2]  Andrzej Skowron,et al.  Rough mereology: A new paradigm for approximate reasoning , 1996, Int. J. Approx. Reason..

[3]  David J. Saab,et al.  Logic and Abstraction as Capabilities of the Mind: Reconceptualizations of Computational Approaches to the Mind , 2010 .

[4]  Andrew Targowski.  Civilization Wisdom in the 21st Century , 2009 .

[5]  Lech Polkowski.  Rough-fuzzy-neurocomputing based on rough mereological calculus of granules , 2005, Int. J. Hybrid Intell. Syst..

[6]  Andrzej Skowron,et al.  Information granules: Towards foundations of granular computing , 2001 .

[7]  Yingxu Wang.  Novel Approaches in Cognitive Informatics and Natural Intelligence , 2008 .

[8]  Chen Yan,et al.  Adaptive Narration in Multiplayer Ubiquitous Games , 2009, Int. J. Cogn. Informatics Nat. Intell..

[9]  D. Davis.  Visions of mind : architectures for cognition and affect , 2005 .

[10]  Andrew Targowski.  Cognitive Informatics and Wisdom Development: Interdisciplinary Approaches , 2010 .

[11]  Amar Ramdane-Cherif.  Toward Autonomic Computing: Adaptive Neural Network for Trajectory Planning , 2007, Int. J. Cogn. Informatics Nat. Intell..

[12]  Lech Polkowski,et al.  A Note on 3-valued Rough Logic Accepting Decision Rules , 2004, Fundam. Informaticae.

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

[14]  Andrzej Skowron,et al.  Rough Mereological Calculi of Granules: A Rough Set Approach To Computation , 2001, Comput. Intell..

[15]  M. Gluck,et al.  Interactive memory systems in the human brain , 2001, Nature.

[16]  Sankar K. Pal,et al.  Soft data mining, computational theory of perceptions, and rough-fuzzy approach , 2004, Inf. Sci..

[17]  Jerzy W. Grzymala-Busse,et al.  Rough Sets , 1995, Commun. ACM.

[18]  Colin Tattersall,et al.  Swarm-Based Wayfinding Support in Open and Distance Learning , 2005 .

[19]  Jordi Vallverd,et al.  Thinking Machines and the Philosophy of Computer Science: Concepts and Principles , 2010 .