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

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

by Ling Zhang, Bo Zhang
Quotient Space Based Problem Solving: A Theoretical Foundation of Granular Computing

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

by Ling Zhang, Bo Zhang

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$129.95 

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Overview

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

Product Details

ISBN-13: 9780124104433
Publisher: Morgan Kaufmann Publishers
Publication date: 01/30/2014
Sold by: Barnes & Noble
Format: eBook
Pages: 396
File size: 20 MB
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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.

Table of Contents

Chapter 1 Problem Representation Chapter 2 Hierarchy and Multi-granular Computing Chapter 3 Information Synthesis in Multi-granular Computing Chapter 4 Reasoning in Multi-granular Computing Chapter 5 Automatic Spatial Planning Chapter 6 Statistical Heuristic Search Chapter 7 the Expansion of Quotient Space Theory Addenda A: Some Concepts and Properties of Point Set Topology Addenda B: Some Concepts and Properties of Integral and Statistical Inference

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The latest research and developments in granular computing presented with an applications-based focus.

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