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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.    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.

Quotient Space Based Problem Solving

POST SECONDARY FOUR YEAR

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QUOTIENT SPACE BASED PROBLEM SOLVING

Duration

Duration Unit Of Measure

Transaction Type

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
Contents.
Preface.
1: Problem Representations.
2: Hierarchy and Multi-Granular Computing.
3: Information Synthesis in Multi-Granular Computing.
4: Reasoning in Multi-Granular Worlds.
5: Automatic Spatial Planning.
6: Statistical Heuristic Search.
7: The Expansion of Quotient Space Theory.
8: Some Concepts and Properties of Point Set Topology.
9: Some Concepts and Properties of Integral and Statistical Inference.
References.
Index.

Quotient Space Based Problem Solving.css-1p8rvzy{position:absolute;padding-left:8px;}

Quotient Space Based Problem Solving