Quotient Space Based Problem Solving: A Theoretical Foundation of Granular Computing

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9780124103870: Quotient Space Based Problem Solving: A Theoretical Foundation of Granular Computing

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

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    From the Back Cover:

    Quotient Space Based Problem Solving-A Theoretical Foundation of Granular Computing

    Research results obtained by the authors form the basis of this volume. The motivation behind this research is the belief that more human-like characteristics in problem solving should be involved in a formal representation in order to achieve better performance for computer-based problem solvers. While much of the current material available is presented in the language of mathematics, including elementary topology, set theory and statistics, Quotient Space Based Problem Solving presents key concepts and techniques, including basic definitions and theorems in accessible, practical terms before the relevant discussions. Each topic is introduced by simple examples and applications. Quotient Space Based Problem Solving is designed for graduate students, research fellows and technicians in Computer Science, especially Artificial Intelligence, and those concerned with computerized problem solving.

    • 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.

    Editors

    Ling Zhang

    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.

    Bo Zhang

    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.

    About the Author:

    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.

    "About this title" may belong to another edition of this title.

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