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Ling Zhang, Bo Zhang - Quotient Space Based Problem Solving, Inbunden

Inbunden, Engelska, 2014

Quotient Space Based Problem Solving

A Theoretical Foundation of Granular Computing

Av Ling Zhang, Bo Zhang

1359 kr

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Beskrivning

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.



    • Explains the theory of hierarchical problem solving, its computational complexity, and discusses the principle and applications of multi-granular computing
    • Describes a human-like, theoretical framework using quotient space theory, that will be of interest to researchers in artificial intelligence
    • Provides many applications and examples in the engineering and computer science area
    • Includes complete coverage of planning, heuristic search and coverage of strictly mathematical models
    Produktinformation
    • Utgivningsdatum: 2014-02-13
    • Mått: 191 x 235 x 22 mm
    • Vikt: 1 070 g
    • Format: Inbunden
    • Språk: Engelska
    • Antal sidor: 396
    • Förlag: Elsevier Science
    • ISBN: 9780124103870
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    Mer information

    Professor Ling Zhang is currently with the Department of Computer Science at Anhui University in Hefei, China. His main interests are artificial intelligence, machine learning, neural networks, genetic algorithms and computational intelligence. Professor Bo Zhang is currently with the Computer Science and Technology Department at Tsinghua University in Beijing, China, He is a Fellow of Chinese Academy of Sciences. His main research interests include artificial intelligence, robotics, intelligent control and pattern recognition. He has published over 150 papers and 3 monographs in these fields.

    Recensioner i media

    "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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