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 hierarc...
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
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Oxford :
Morgan Kaufmann
2014.
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| Edición: | 1st ed |
| Colección: | Gale eBooks
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| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627879906719 |
Tabla de Contenidos:
- Front Cover; Quotient Space Based Problem Solving: A Theoretical Foundation of Granular Computing; Copyright; Contents; Preface; Chapter 1 - Problem Representations; 1.1 Problem Solving; 1.2 World Representations at Different Granularities; 1.3 The Acquisition of Different Grain-Size Worlds; 1.4 The Relation Among Different Grain Size Worlds; 1.5 Property-Preserving Ability; 1.6 Selection and Adjustment of Grain-Sizes; Example 1.15; 1.7 Conclusions; Chapter 2 - Hierarchy and Multi-Granular Computing; 2.1 The Hierarchical Model; 2.2 The Estimation of Computational Complexity
- 2.3 The Extraction of Information on Coarsely Granular Levels2.4 Fuzzy Equivalence Relation and Hierarchy; 2.5 The Applications of Quotient Space Theory; 2.6 Conclusions; Chapter 3 - Information Synthesis in Multi-Granular Computing; 3.1 Introduction; 3.2 The Mathematical Model of Information Synthesis; 3.3 The Synthesis of Domains; 3.4 The Synthesis of Topologic Structures; 3.5 The Synthesis of Semi-Order Structures; 3.6 The Synthesis of Attribute Functions; Chapter 4 - Reasoning in Multi-Granular Worlds; 4.1 Reasoning Models; 4.2 The Relation Between Uncertainty and Granularity
- 4.3 Reasoning (Inference) Networks (1)4.4 Reasoning Networks (2); 4.5 Operations and Quotient Structures; 4.6 Qualitative Reasoning; 4.7 Fuzzy Reasoning Based on Quotient Space Structures; Chapter 5 - Automatic Spatial Planning; 5.1 Automatic Generation of Assembly Sequences; 5.2 The Geometrical Methods of Motion Planning; 5.3 The Topological Model of Motion Planning; 5.4 Dimension Reduction Method; 5.5 Applications; Chapter 6 - Statistical Heuristic Search; 6.1 Statistical Heuristic Search; 6.2 The Computational Complexity; 6.3 The Discussion of Statistical Heuristic Search
- A.6 ConnectednessA.7 Order-Relation, Galois Connected and Closure Space; Addenda B - Some Concepts and Properties of Integral and Statistical Inference; B.1 Some Properties of Integral; B.2 Central Limit Theorem; B.3 Statistical Inference; References; Index
