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

✍ Scribed by Ling Zhang and Bo Zhang (Auth.)

Publisher: Morgan Kaufmann
Year: 2014
Tongue: English
Leaves: 380
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Content:
Front Matter, Page iii
Copyright, Page iv
Preface, Pages xi-xiii
Chapter 1 - Problem Representations, Pages 1-43
Chapter 2 - Hierarchy and Multi-Granular Computing, Pages 45-103
Chapter 3 - Information Synthesis in Multi-Granular Computing, Pages 105-127
Chapter 4 - Reasoning in Multi-Granular Worlds, Pages 129-191
Chapter 5 - Automatic Spatial Planning, Pages 193-248
Chapter 6 - Statistical Heuristic Search, Pages 249-297
Chapter 7 - The Expansion of Quotient Space Theory, Pages 299-331
Addenda A - Some Concepts and Properties of Point Set Topology, Pages 333-362
Addenda B - Some Concepts and Properties of Integral and Statistical Inference, Pages 363-374
References, Pages 375-379
Index, Pages 381-382

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