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A Logic Approach to Granular Computing

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  • Bing Zhou

    (University of Regina, Canada)

Abstract

Granular computing is an emerging field of study that attempts to formalize and explore methods and heuristics of human problem solving with multiple levels of granularity and abstraction. A fundamental issue of granular computing is the representation and utilization of granular structures. The main objective of this article is to examine a logic approach to address this issue. Following the classical interpretation of a concept as a pair of intension and extension, we interpret a granule as a pair of a set of objects and a logic formula describing the granule. The building blocks of granular structures are basic granules representing an elementary concept or a piece of knowledge. They are treated as atomic formulas of a logic language. Different types of granular structures can be constructed by using logic connectives. Within this logic framework, we show that rough set analysis (RSA) and formal concept analysis (FCA) can be interpreted uniformly. The two theories use multilevel granular structures but differ in their choices of definable granules and granular structures.

Suggested Citation

  • Bing Zhou, 2008. "A Logic Approach to Granular Computing," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 2(2), pages 63-79, April.
    • Handle: RePEc:igg:jcini0:v:2:y:2008:i:2:p:63-79
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    Cited by:

    1. Sudarsan Biswas & Neepa Biswa & Kartick Chandra Mondal, 2019. "Parallel and Distributed Association Rule Mining Algorithms: A recent survey," Information Management and Computer Science (IMCS), Zibeline International Publishing, vol. 2(1), pages 15-24, September.

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