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 computingDescribes a human-like, theoretical framework using quotient space theory, that will be of interest to researchers in artificial intelligenceProvides many applications and examples in the engineering and computer science areaIncludes complete coverage of planning, heuristic search and coverage of strictly mathematical models

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