Quotient Space Based Problem Solving

A Theoretical Foundation of Granular Computing

By: Ling Zhang, Bo Zhang

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Hardcover | 25 February 2014 | Edition Number 1

At a Glance

Hardcover
396 Pages

Dimensions(cm)
23.5 x 19.05 x 2.54

Hardcover

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Quotient Space Based Problem Solving provides an in-depth treatment of hierarchical problem solving, computational complexity, and the principles and applications of multi-granular computing, including inference, information fusing, planning, and heuristic search. Drawing upon years of academic research and using numerous examples and illustrative applications, the authors, Ling Zhang and Bo Zhang provide a unique guide to computerized problem solving and granular computing. This book is a valuable guide to graduate students, research fellows, and academics specializing in artificial intelligence or concerned with computerized problem solving and granular computing. It explains the theory of hierarchical problem solving, its computational complexity, and discusses the principle and applications of multi-granular computing. It describes a human-like, theoretical framework using quotient space theory, that will be of interest to researchers in artificial intelligence. It provides many applications and examples in the engineering and computer science area. It includes complete coverage of planning, heuristic search and coverage of strictly mathematical models.

Industry Reviews

"The entire book is devoted to formalize and automate...a theory of granular computing, which is essentially based on quotient spaces." --Zentralblatt MATH "... aimed primarily at graduate students (and academicians) with strong mathematical maturity and an interest in mathematical modeling in the fields around artificial intelligence (AI)." --Computing Reviews, November 2014

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