Modeling Decisions for Artificial Intelligence

Decision modeling is a key area in the developing field of AI, and this timely work connects researchers and professionals with the very latest research. It constitutes the refereed proceedings of the 4th International Conference on Modeling Decisions for Artificial Intelligence, held in Kitakyushu, Japan, in August 2007. The 42 revised full papers presented together with 4 invited lectures are devoted to theory and tools, as well as applications.

Inhalt

Invited Papers.- An Overview of Fuzzy Relational Calculus and Its Applications.- Golden Quadruplet: Optimization - Inequality - Identity - Operator.- Algorithms for String Pattern Discovery.- Voting in the Medieval Papacy and Religious Orders.- Decision Making.- Static and Dynamic Coalition Formation in Group-Choice Decision Making.- A Multicriteria Fuzzy System Using Residuated Implication Operators and Fuzzy Arithmetic.- A Behavioral Analysis in Decision Making Using Weather Information with the Fuzzy Target Based Decision Model.- Group Decision Making: From Consistency to Consensus.- Weighting Individual Opinions in Group Decision Making.- An Active Learning Method Based on Most Possible Misclassification Sampling Using Committee.- Research on Next Generation Grids Using a Fuzzy Assessment Method.- Combining Prioritized Decisions in Classification.- An Aggregation of Agents, Roles and Coalition Formation to Support Collaborative and Dynamic Organizations.- Non Additive Measures and Concept Lattices.- Multidimensional Fuzzy Integrals.- Lindig's Algorithm for Concept Lattices over Graded Attributes.- A Version of Lebesgue Decomposition Theorem for Non-additive Measure.- Trees in Concept Lattices.- An Axiomatization of Shapley Values of Games on Set Systems.- Clustering and Rough Sets.- Formulation of Fuzzy c-Means Clustering Using Calculus of Variations.- CWC: A Clustering-Based Feature Weighting Approach for Text Classification.- A Novel Spatial Clustering Algorithm with Sampling.- Algorithms for Sequential Extraction of Clusters by Possibilistic Clustering.- Fuzzy c-Means for Data with Tolerance Defined as Hyper-Rectangle.- Kernel Functions Based on Fuzzy Neighborhoods and Agglomerative Clustering.- c-Means Clustering on the Multinomial Manifold.- On a Rough Sets Based Tool for Generating Rules from Data with Categorical and Numerical Values.- Applying Rough Sets to Information Tables Containing Probabilistic Values.- Soft Computing.- Fuzzy Extension of Estimations with Randomness: The Perception-Based Approach.- Boltzmann Machine Incorporated Hybrid Neural Fuzzy System for Hardware/Software Partitioning in Embedded System Design.- Artificial Bee Colony (ABC) Optimization Algorithm for Training Feed-Forward Neural Networks.- A Multi-supplier and Return-Policy Newsboy Model with Limited Budget and Minimum Service Level by Using GA.- Performance Enhancement of RBF Networks in Classification by Removing Outliers in the Training Phase.- An Evolutionary Algorithm with Diversified Crossover Operator for the Heterogeneous Probabilistic TSP.- Applications.- Ordered Data Set Vectorization for Linear Regression on Data Privacy.- A Public-Key Protocol for Social Networks with Private Relationships.- An Incentive-Based System for Information Providers over Peer-to-Peer Mobile Ad-Hoc Networks.- Classification of Normal and Tumor Tissues Using Geometric Representation of Gene Expression Microarray Data.- A Seed-Based Method for Predicting Common Secondary Structures in Unaligned RNA Sequences.- Automatic Segmentation of Neoplastic Hepatic Disease Symptoms in CT Images.- A Robust Localization Method for Mobile Robots Based on Ceiling Landmarks.- Robust Parameter Decision-Making Based on Multidisciplinary Knowledge Model.- Resolution of Singularities and Stochastic Complexity of Complete Bipartite Graph-Type Spin Model in Bayesian Estimation.- A Study of Emotion Recognition and Its Applications.- Error Detection and Correction Based on Chinese Phonemic Alphabet in Chinese Text.- Mining Frequent Diamond Episodes from Event Sequences.- Modeling Decisions for the Time-Dependent Optimal Lane Configuration Policy with Queueing Theory and Mathematical Programming.