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Computer Science - Theoretical Computer Science | The Puzzle of Granular Computing

The Puzzle of Granular Computing

Apolloni, B., Pedrycz, W., Bassis, S., Malchiodi, D.

2008, XVIII, 495 p.

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  • Highly unique and relevant book presenting the key fundamentals and practice of Granular Computing
  • Brings the fundamental issues of information granularity and statistical inference into a coherent, unified, and highly operational framework

Rem tene, verba sequentur (Gaius J. Victor, Rome VI century b.c.)

The ultimate goal of this book is to bring the fundamental issues of information granularity, inference tools and problem solving procedures into a coherent, unified, and fully operational framework. The objective is to offer the reader a comprehensive, self-contained, and uniform exposure to the subject.The strategy is to isolate some fundamental bricks of Computational Intelligence in terms of key problems and methods, and discuss their implementation and underlying rationale within a well structured and rigorous conceptual framework as well as carefully related to various application facets. The main assumption is that a deep understanding of the key problems will allow the reader to compose into a meaningful mosaic the puzzle pieces represented by the immense variety of approaches present in the literature and in the computational practice. All in all, the main approach advocated in the monograph consists of a sequence of steps offering solid conceptual fundamentals, presenting a carefully selected collection of design methodologies, discussing a wealth of development guidelines, and exemplifying them with a pertinent, accurately selected illustrative material.

Content Level » Research

Keywords » Cluster - Computaional Intelligence - Fuzzy - Fuzzy Sets - Granular Computing - Granular Constructs - algorithm - algorithms - construction - fuzzy set - modeling

Related subjects » Computational Intelligence and Complexity - Software Engineering - Theoretical Computer Science

Table of contents 

The General Framework.- Granule Formation Around Data.- I: Algorithmic Inference.- Modeling Samples.- Inferring from Samples.- II: The Development of Fuzzy Sets.- Construction of Information Granules: From Data and Perceptions to Information Granules.- Estimating Fuzzy Sets.- III: Expanding Granula into Boolean Functions.- The Clustering Problem.- Suitably Representing Data.- IV: Directing Populations.- The Main Paradigms of Social Computation.- If also Ants Are Able....- V: Granular Constructs.- Granular Constructs.- Identifying Fuzzy Rules.- A Conceptual Synthesis.- Knowledge Engineering.

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