Integrated uncertainty in knowledge modelling and decision making : 4th International Symposium, IUKM 2015, Nha Trang, Vietnam, October 15-17, 2015, Proceedings / edited by Van-Nam Huynh, Masahiro Inuiguchi, Thierry Denoeux.
Material type:
TextSeries: Lecture notes in computer science. Lecture notes in artificial intelligence ; ; 9376. | LNCS sublibrary. SL 7, Artificial intelligence.Publisher: Cham : Springer, 2015Description: 1 online resource (xiv, 495 pages) : illustrationsContent type: - text
- computer
- online resource
- 9783319251356
- 331925135X
- IUKM 2015
- Uncertainty (Information theory) -- Congresses
- Computer science
- Artificial intelligence
- Electronic Data Processing
- Artificial Intelligence
- Incertitude (Théorie de l'information) -- Congrès
- Informatique
- Intelligence artificielle
- artificial intelligence
- Artificial intelligence
- Computer science
- Uncertainty (Information theory)
- 006.3 23
- Q375
- Q334-342
- TJ210.2-211.495
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
eBook
|
e-Library | eBook LNCS | Available |
This book constitutes the refereed proceedings of the 4th International Symposium on Integrated Uncertainty in Knowledge Modeling and Decision Making, IUKM 2015, held in Nha Trang, Vietnam, in October 2015. The 40 revised full papers were carefully reviewed and selected from 58 submissions and are presented together with three keynote and invited talks. The papers provide a wealth of new ideas and report both theoretical and applied research on integrated uncertainty modeling and management.
Includes author index.
Intro; Preface; Organization; Epistemic Uncertainty Modeling: The-state-of-the-art; 1 Introduction; 2 Information Measures; 3 Fuzzy Measures; 4 Belief Functions; 5 Possibility Measures; 6 Imprecise Probabilities; 7 Conclusions; References; Fuzzy Sets, Multisets, and Rough Approximations; 1 Multisets; 2 Fuzzy Multisets; 3 Rough Approximations; 4 Conclusion; References; What Is Fuzzy Natural Logic Abstract; References; Combining Fuzziness and Context Sensitivity in Game Based Models of Vague Quantification; 1 Introduction; 2 Classifying Vague and Fuzzy Quantifiers
3 Problems with Fuzzy Models of Vague Quantifiers4 Giles's Game for Łukasiewicz Logic; 5 From Type I to Type II Quantifiers Via Precisifications; 6 From Type III to Type IV Quantifiers: Random Witnesses; 7 Conclusion; References; A New Model of a Fuzzy Associative Memory; 1 Introduction; 2 Preliminaries; 2.1 Implicative Fuzzy Associative Memory; 2.2 Algebraic Background; 3 Fuzzy Preorders and Their Eigen Sets; 3.1 Fuzzy Preorders and their Upper and Lower Sets; 3.2 Eigen Sets of Fuzzy Preorders and their ``Skeletons''; 4 Fuzzy Preorders and AFIM; 5 Illustration
5.1 Experiments with Abstract Images6 Conclusion; References; Construction of Associative Functions for Several Fuzzy Logics via the Ordinal Sum Theorem; 1 Introduction; 2 Origin of Ordinal Sum Theorem; 3 A Generalization of Ordinal Sums on the Unit Interval [0, 1]; 4 Construction of Logical Connectives on [0, 1]; 4.1 Properties Required for Fuzzy Logical Connectives; 4.2 Realizations of the Properties in the Framework of Ordinal Sum; 5 Applications; 6 Concluding Remarks; References; Appendix; Cognitively Stable Generalized Nash Equilibrium in Static Games with Unawareness; 1 Introduction
2 Model2.1 Static Games with Unawareness; 2.2 Generalized Nash Equilibrium; 3 Cognitive Stability; 3.1 Problem; 3.2 Definition; 3.3 Properties; 4 Conclusion; References; Maximum Lower Bound Estimation of Fuzzy Priority Weights from a Crisp Comparison Matrix; 1 Introduction; 2 Lower Bound Based Interval AHP; 3 Estimating Fuzzy Weight; 4 Numerical Examples; 5 Conclusion; References; Logarithmic Conversion Approach to the Estimation of Interval Priority Weights from a Pairwise Comparison Matrix; 1 Introduction; 2 Interval AHP; 3 Logarithmic Conversion Approach; 4 Numerical Experiments
4.1 Outline4.2 Experiments with a Logarithmic Normal Distribution; 4.3 Experiments with True Interval Priority Weights; 5 Concluding Remarks; References; An Effective Method for Optimality Test Over Possible Reaction Set for Maximin Solution of Bilevel Linear Programming with Ambiguous Lower-Level Objective Function; 1 Introduction; 2 Problem Formulation; 3 Proposed Solution Methods; 3.1 K-th Best Method; 3.2 Rational Reactions and Possible Optimality Test; 3.3 Local Optimality Test; 3.4 Global Optimality Test; 4 Numerical Experiments; 4.1 Problem Generation; 4.2 Numerical Results
English.