书籍详情
影响图的扩展及其应用(英文版)
作者:周丽华 著
出版社:科学出版社
出版时间:2018-03-01
ISBN:9787030316776
定价:¥58.00
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内容简介
影响图是不确定环境中描述复杂决策问题的图模型,它表达了变量间的依赖关系、条件独立关系和决策者的偏好信息。目前,影响图已成为一种流行的标准建模工具。然而,现实中的决策环境复杂多样,在一些应用中现有的影响图还不足以满足要求,因此有必要对它们进行扩展。本书主要介绍影响图的扩展及应用,包括针对建模无限制决策问题、涉及连续变量的决策问题、涉及非精确变量的决策问题及多Agent 决策问题等方面对影响图的扩展,以及影响图的评价算法和竞争对手私人信息的推测。影响图的扩展有助于增强影响图的表达能力,丰富影响图的类型,提高影响图的适用性,促进影响图的发展,扩大影响图的应用领域
作者简介
暂缺《影响图的扩展及其应用(英文版)》作者简介
目录
Contents
Preface
Chapter1 Introduction 1
1.1 Motivations 1
1.2 Outline of the Book 2
Chapter2 Influence Diagrams 3
2.1 Introduction 3
2.2 Preliminary 3
2.3 Influence Diagrams 9
2.3.1 Th e graphical component of an ID 9
2.3.2 The numerical component of an ID 11
2.4 Conclusion 14
Chapter3 The Extensions of Influence Diagrams 15
3.1 Introduction 15
3.2 Unconstrained Influence Diagrams (UIDs) 17
3.3 Limited Memory Influence Diagrams (LIMIDs) 19
3.4 Mixtures of Truncated Exponentials Influence Diagrams (MTE IDs) 20
3.5 Possibilistic Influence Diagrams (PIDs) 22
3.6 Interval-Valued Influence Diagrams (IIDs) 25
3.6.1 Bound-limited weak conditional interval probability 29
3.6.2 Influence diagrams with interval-valued parameters (BIIDs) 32
3.7 Game Theory-Based Influence Diagrams (GIDs) 33
3.7.1 Game theory 34
3.7.2 Game theory-based influence diagrams (GIDs) 36
3.8 Game IDs with Interval-Valued Parameters (GBIIDs) 39
3.9 Conclusion 41
Chapter4 The Evaluation of Influence Diagrams 42
4.1 Introduction 42
4.2 The Concept of Evaluating IDs 43
4.3 Evaluating Standard IDs 46
4.3.1 Arc reversal (AR) 46
4.3.2 Variable elimination(VE) 51
4.3.3 Cooper's method (CM) 54
4.4 Evaluating Interval-Valued IDs 57
4.4.1 Operations for interval-valued potentials 57
4.4.2 Interval arc reversal (IAR) 57
4.4.3 Interval variable elimination (IVE) 62
4.4.4 Chance variable and arc reversal elimination in IIDs by linear programming 65
4.4.5 Interval Cooper's method (ICM) for evaluating BIIDs 69
4.5 Evaluating GIDs 79
4.5.1 Concepts 79
4.5.2 The design of the genetic algorithm 82
4.5.3 The algorithm for evaluating GIDs (EAGIDs) 84
4.6 Evaluating Game IDs with Interval-Valued Parameters (GBIIDs) 89
4.6.1 Solving games with interval-valued utilities 89
4.6.2 Computing strategy utilities for utility nodes shared by multiple decision makers 90
4.6.3 Selecting the strategy with maximal interval-valued expect utility 92
4.7 Conclusion 93
Chapter5 Applications of Influence Diagrams 95
5.1 Finding Optimal Strategies for a Decision Maker by a BIID 95
5.2 Applying Influence Diagrams to Infer Rival's Private Information 99
5.2.1 The type of rival's private information 100
5.2.2 Inferring rival's private information 102
5.2.3 Experiments 104
5.3 Conclusion 107
References 109
Preface
Chapter1 Introduction 1
1.1 Motivations 1
1.2 Outline of the Book 2
Chapter2 Influence Diagrams 3
2.1 Introduction 3
2.2 Preliminary 3
2.3 Influence Diagrams 9
2.3.1 Th e graphical component of an ID 9
2.3.2 The numerical component of an ID 11
2.4 Conclusion 14
Chapter3 The Extensions of Influence Diagrams 15
3.1 Introduction 15
3.2 Unconstrained Influence Diagrams (UIDs) 17
3.3 Limited Memory Influence Diagrams (LIMIDs) 19
3.4 Mixtures of Truncated Exponentials Influence Diagrams (MTE IDs) 20
3.5 Possibilistic Influence Diagrams (PIDs) 22
3.6 Interval-Valued Influence Diagrams (IIDs) 25
3.6.1 Bound-limited weak conditional interval probability 29
3.6.2 Influence diagrams with interval-valued parameters (BIIDs) 32
3.7 Game Theory-Based Influence Diagrams (GIDs) 33
3.7.1 Game theory 34
3.7.2 Game theory-based influence diagrams (GIDs) 36
3.8 Game IDs with Interval-Valued Parameters (GBIIDs) 39
3.9 Conclusion 41
Chapter4 The Evaluation of Influence Diagrams 42
4.1 Introduction 42
4.2 The Concept of Evaluating IDs 43
4.3 Evaluating Standard IDs 46
4.3.1 Arc reversal (AR) 46
4.3.2 Variable elimination(VE) 51
4.3.3 Cooper's method (CM) 54
4.4 Evaluating Interval-Valued IDs 57
4.4.1 Operations for interval-valued potentials 57
4.4.2 Interval arc reversal (IAR) 57
4.4.3 Interval variable elimination (IVE) 62
4.4.4 Chance variable and arc reversal elimination in IIDs by linear programming 65
4.4.5 Interval Cooper's method (ICM) for evaluating BIIDs 69
4.5 Evaluating GIDs 79
4.5.1 Concepts 79
4.5.2 The design of the genetic algorithm 82
4.5.3 The algorithm for evaluating GIDs (EAGIDs) 84
4.6 Evaluating Game IDs with Interval-Valued Parameters (GBIIDs) 89
4.6.1 Solving games with interval-valued utilities 89
4.6.2 Computing strategy utilities for utility nodes shared by multiple decision makers 90
4.6.3 Selecting the strategy with maximal interval-valued expect utility 92
4.7 Conclusion 93
Chapter5 Applications of Influence Diagrams 95
5.1 Finding Optimal Strategies for a Decision Maker by a BIID 95
5.2 Applying Influence Diagrams to Infer Rival's Private Information 99
5.2.1 The type of rival's private information 100
5.2.2 Inferring rival's private information 102
5.2.3 Experiments 104
5.3 Conclusion 107
References 109
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