Rough mereological calculi of granules: A rough set approach to computation

Citation
L. Polkowski et A. Skowron, Rough mereological calculi of granules: A rough set approach to computation, COMPUT INTE, 17(3), 2001, pp. 472-492
Citations number
37
Categorie Soggetti
AI Robotics and Automatic Control
Journal title
COMPUTATIONAL INTELLIGENCE
ISSN journal
08247935 → ACNP
Volume
17
Issue
3
Year of publication
2001
Pages
472 - 492
Database
ISI
SICI code
0824-7935(200108)17:3<472:RMCOGA>2.0.ZU;2-O
Abstract
Rough Mereology is a paradigm allowing for a synthesis of main ideas of two potent paradigms for reasoning under uncertainty: Fuzzy Set Theory and Rou gh Set Theory. Approximate reasoning is based in this paradigm on the predi cate of being a part to a degree. We present applications of Rough Mereolog y to the important theoretical idea put forth by Lotfi Zadeh (1996, 1997), i.e., Granularity of Knowledge: We define granules of knowledge by means of the operator of mereological class and we extend the idea of a granule ove r complex objects like decision rules as well as decision algorithms. We ap ply these notions and methods in the distributed environment discussing com plex problems of knowledge and granule fusion. We express the mechanism of complex granule formation by means of a formal grammar called Synthesis Gra mmar defined over granules of knowledge, granules of classifying rules, or over granules of classifying algorithms. We finally propose hybrid rough-ne ural schemes bridging rough and neural computations.(1)