Symbolic and quantitative approaches to reasoning with uncertainty : 8th European conference, ECSQARU 2005, Barcelona, Spain, July 6-8, 2005 ; proceedings
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書誌事項
Symbolic and quantitative approaches to reasoning with uncertainty : 8th European conference, ECSQARU 2005, Barcelona, Spain, July 6-8, 2005 ; proceedings
（Lecture notes in computer science, 3571 . Lecture notes in artificial intelligence）
Springer, c2005
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
These are the proceedings of the 8th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2005, held in Barcelona (Spain), July 6-8, 2005. The ECSQARU conferences are biennial and have become a major forum for advances in the theory and practice of r- soning under uncertainty. The ?rst ECSQARU conference was held in Marseille (1991), and after in Granada (1993), Fribourg (1995), Bonn (1997), London (1999), Toulouse (2001) and Aalborg (2003). The papers gathered in this volume were selected out of 130 submissions, after a strict review process by the members of the Program Committee, to be presented at ECSQARU 2005. In addition, the conference included invited lectures by three outstanding researchers in the area, Seraf ?n Moral (Imprecise Probabilities), Rudolf Kruse (Graphical Models in Planning) and J er ome Lang (Social Choice). Moreover, the application of uncertainty models to real-world problems was addressed at ECSQARU 2005 by a special session devoted to s- cessful industrial applications, organized by Rudolf Kruse. Both invited lectures and papers of the special session contribute to this volume. On the whole, the programme of the conference provided a broad, rich and up-to-date perspective of the current high-level research in the area which is re?ected in the contents of this volume. IwouldliketowarmlythankthemembersoftheProgramCommitteeandthe additional referees for their valuable work, the invited speakers and the invited session organizer.
目次
Invited Papers.- Imprecise Probability in Graphical Models: Achievements and Challenges.- Knowledge-Based Operations for Graphical Models in Planning.- Some Representation and Computational Issues in Social Choice.- Bayesian Networks.- Nonlinear Deterministic Relationships in Bayesian Networks.- Penniless Propagation with Mixtures of Truncated Exponentials.- Approximate Factorisation of Probability Trees.- Abductive Inference in Bayesian Networks: Finding a Partition of the Explanation Space.- Alert Systems for Production Plants: A Methodology Based on Conflict Analysis.- Hydrologic Models for Emergency Decision Support Using Bayesian Networks.- Graphical Models.- Probabilistic Graphical Models for the Diagnosis of Analog Electrical Circuits.- Qualified Probabilistic Predictions Using Graphical Models.- A Decision-Based Approach for Recommending in Hierarchical Domains.- Learning Causal Networks.- Scalable, Efficient and Correct Learning of Markov Boundaries Under the Faithfulness Assumption.- Discriminative Learning of Bayesian Network Classifiers via the TM Algorithm.- Constrained Score+(Local)Search Methods for Learning Bayesian Networks.- On the Use of Restrictions for Learning Bayesian Networks.- Foundation for the New Algorithm Learning Pseudo-Independent Models.- Planning.- Optimal Threshold Policies for Operation of a Dedicated-Platform with Imperfect State Information - A POMDP Framework.- APPSSAT: Approximate Probabilistic Planning Using Stochastic Satisfiability.- Causality and Independence.- Racing for Conditional Independence Inference.- Causality, Simpson's Paradox, and Context-Specific Independence.- A Qualitative Characterisation of Causal Independence Models Using Boolean Polynomials.- Preference Modelling and Decision.- On the Notion of Dominance of Fuzzy Choice Functions and Its Application in Multicriteria Decision Making.- An Argumentation-Based Approach to Multiple Criteria Decision.- Algorithms for a Nonmonotonic Logic of Preferences.- Expressing Preferences from Generic Rules and Examples - A Possibilistic Approach Without Aggregation Function.- On the Qualitative Comparison of Sets of Positive and Negative Affects.- Argumentation Systems.- Symmetric Argumentation Frameworks.- Evaluating Argumentation Semantics with Respect to Skepticism Adequacy.- Logic of Dementia Guidelines in a Probabilistic Argumentation Framework.- Argument-Based Expansion Operators in Possibilistic Defeasible Logic Programming: Characterization and Logical Properties.- Gradual Valuation for Bipolar Argumentation Frameworks.- On the Acceptability of Arguments in Bipolar Argumentation Frameworks.- Inconsistency Handling.- A Modal Logic for Reasoning with Contradictory Beliefs Which Takes into Account the Number and the Reliability of the Sources.- A Possibilistic Inconsistency Handling in Answer Set Programming.- Measuring the Quality of Uncertain Information Using Possibilistic Logic.- Remedying Inconsistent Sets of Premises.- Measuring Inconsistency in Requirements Specifications.- Belief Revision and Merging.- Belief Revision of GIS Systems: The Results of REV!GIS.- Multiple Semi-revision in Possibilistic Logic.- A Local Fusion Method of Temporal Information.- Mediation Using m-States.- Combining Multiple Knowledge Bases by Negotiation: A Possibilistic Approach.- Conciliation and Consensus in Iterated Belief Merging.- An Argumentation Framework for Merging Conflicting Knowledge Bases: The Prioritized Case.- Belief Functions.- Probabilistic Transformations of Belief Functions.- Contextual Discounting of Belief Functions.- Fuzzy Models.- Bilattice-Based Squares and Triangles.- A New Algorithm to Compute Low T-Transitive Approximation of a Fuzzy Relation Preserving Symmetry. Comparisons with the T-Transitive Closure.- Computing a Transitive Opening of a Reflexive and Symmetric Fuzzy Relation.- Generating Fuzzy Models from Deep Knowledge: Robustness and Interpretability Issues.- Analysis of the TaSe-II TSK-Type Fuzzy System for Function Approximation.- Many-Valued Logical Systems.- Non-deterministic Semantics for Paraconsistent C-Systems.- Multi-valued Model Checking in Dense-Time.- Brun Normal Forms for Co-atomic ?ukasiewicz Logics.- Poset Representation for Goedel and Nilpotent Minimum Logics.- Uncertainty Logics.- Possibilistic Inductive Logic Programming.- Query Answering in Normal Logic Programs Under Uncertainty.- A Logical Treatment of Possibilistic Conditioning.- A Zero-Layer Based Fuzzy Probabilistic Logic for Conditional Probability.- A Logic with Coherent Conditional Probabilities.- Probabilistic Description Logic Programs.- Probabilistic Reasoning.- Coherent Restrictions of Vague Conditional Lower-Upper Probability Extensions.- Type Uncertainty in Ontologically-Grounded Qualitative Probabilistic Matching.- Some Theoretical Properties of Conditional Probability Assessments.- Unifying Logical and Probabilistic Reasoning.- Reasoning Models Under Uncertainty.- Possibility Theory for Reasoning About Uncertain Soft Constraints.- About the Processing of Possibilistic and Probabilistic Queries.- Conditional Deduction Under Uncertainty.- Heterogeneous Spatial Reasoning.- Uncertainty Measures.- A Notion of Comparative Probabilistic Entropy Based on the Possibilistic Specificity Ordering.- Consonant Random Sets: Structure and Properties.- Comparative Conditional Possibilities.- Second-Level Possibilistic Measures Induced by Random Variables.- Probabilistic Classifiers.- Hybrid Bayesian Estimation Trees Based on Label Semantics.- Selective Gaussian Naive Bayes Model for Diffuse Large-B-Cell Lymphoma Classification: Some Improvements in Preprocessing and Variable Elimination.- Towards a Definition of Evaluation Criteria for Probabilistic Classifiers.- Methods to Determine the Branching Attribute in Bayesian Multinets Classifiers.- Classification and Clustering.- Qualitative Inference in Possibilistic Option Decision Trees.- Partially Supervised Learning by a Credal EM Approach.- Default Clustering from Sparse Data Sets.- New Technique for Initialization of Centres in TSK Clustering-Based Fuzzy Systems.- Industrial Applications.- Learning Methods for Air Traffic Management.- Molecular Fragment Mining for Drug Discovery.- Automatic Selection of Data Analysis Methods.
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