Rough-Granular Computing in Human-Centric Information Processing

2009 ◽  
pp. 23-42 ◽  
Author(s):  
Andrzej Jankowski ◽  
Andrzej Skowron
Keyword(s):  
Information Processing ◽  
Granular Computing

Human-Inspired Granular Computing

2010 ◽  
pp. 1-15 ◽  
Author(s):  
Yiyu Yao
Keyword(s):  
Information Processing ◽  
Problem Solving ◽  
Granular Computing ◽  
Hierarchical Structures ◽  
Structured Information ◽  
Multiple Levels ◽  
Structured Problem Solving ◽  
Structured Approach ◽  
Machine Problem

In this chapter, I explore a view of granular computing as a paradigm of human-inspired problem solving and information processing, covering human-oriented studies and machine-oriented studies. By exploring the notion of multiple levels of granularity, one can identify, examine and formalize a special family of principles, strategies, heuristics, and methods that are commonly used by humans in daily problem solving. The results may then be used for human and machine problem solving, as well as for implementing human-inspired approaches in machines and systems. The triarchic theory of granular computing unifies both types of studies from three perspectives, namely, a philosophy of structured thinking, a methodology of structured problem solving, and a computation paradigm of structured information processing. The stress on multilevel, hierarchical structures makes granular computing a human-inspired and structured approach to problem solving.

On the System Algebra Foundations for Granular Computing

2012 ◽  
pp. 98-121 ◽  
Author(s):  
Yingxu Wang ◽  
Lotfi A. Zadeh ◽  
Yiyu Yao
Keyword(s):  
Information Processing ◽  
Real World ◽  
Granular Computing ◽  
System Modeling ◽  
Computing System ◽  
Granular Systems ◽  
Formal Representation ◽  
Novel Approach ◽  
Algebraic Operations ◽  
Mathematical Foundations

Granular computing studies a novel approach to computing system modeling and information processing. Although a rich set of work has advanced the understanding of granular computing in dealing with the “to be” and “to have” problems of systems, the “to do” aspect of system modeling and behavioral implementation has been relatively overlooked. On the basis of a recent development in denotational mathematics known as system algebra, this paper presents a system metaphor of granules and explores the theoretical and mathematical foundations of granular computing. An abstract system model of granules is proposed in this paper. Rigorous manipulations of granular systems in computing are modeled by system algebra. The properties of granular systems are analyzed, which helps to explain the magnitudes and complexities of granular systems. Formal representation of granular systems for computing is demonstrated by real-world case studies, where concrete granules and their algebraic operations are explained.

Language processing is not a race against time

2016 ◽  
Vol 39 ◽  
Author(s):  
Giosuè Baggio ◽  
Carmelo M. Vicario
Keyword(s):  
Information Processing ◽  
Human Brain ◽  
Language Processing ◽  
Cognitive Functions ◽  
Memory Systems ◽  
Language System ◽  
Moderating Factors

AbstractWe agree with Christiansen & Chater (C&C) that language processing and acquisition are tightly constrained by the limits of sensory and memory systems. However, the human brain supports a range of cognitive functions that mitigate the effects of information processing bottlenecks. The language system is partly organised around these moderating factors, not just around restrictions on storage and computation.

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