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Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 7th European Conference, ECSQARU 2003, Aalborg, Denmark, July 2-5, 2003. Proceedings: Lecture Notes in Computer Science, cartea 2711

Editat de Thomas D. Nielsen, Nevin L. Zhang
en Limba Engleză Paperback – 23 mar 2003

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Specificații

ISBN-13: 9783540404941
ISBN-10: 3540404945
Pagini: 628
Ilustrații: XII, 608 p.
Dimensiuni: 155 x 233 x 33 mm
Greutate: 0.83 kg
Ediția:2003
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Invited Papers.- Qualitative Decision Rules under Uncertainty.- Applications of Latent Class Analysis in Social Science Research.- Foundations of Uncertainty Concepts.- Transformations from Imprecise to Precise Probabilities.- A Representation Theorem and Applications.- On Modal Probability and Belief.- Bayesian Networks.- A Multi-layered Bayesian Network Model for Structured Document Retrieval.- Using Kappas as Indicators of Strength in Qualitative Probabilistic Networks.- Qualitative Bayesian Networks with Logical Constraints.- Introducing Situational Influences in QPNs.- Classification of Aerial Missions Using Hidden Markov Models.- Algorithms for Uncertainty Inference.- Dynamic Importance Sampling Computation in Bayesian Networks.- Morphing the Hugin and Shenoy–Shafer Architectures.- Learning.- Characterization of Inclusion Neighbourhood in Terms of the Essential Graph: Upper Neighbours.- Approximating Conditional MTE Distributions by Means of Mixed Trees.- Effective Dimensions of Partially Observed Polytrees.- Decision Graphs.- Applying Numerical Trees to Evaluate Asymmetric Decision Problems.- Mixed Influence Diagrams.- Decision Making Based on Sampled Disease Occurrence in Animal Herds.- Decision Network Semantics of Branching Constraint Satisfaction Problems.- Belief Functions.- Web of Trust: Applying Probabilistic Argumentation to Public-Key Cryptography.- A Comparison of Methods for Transforming Belief Function Models to Probability Models.- Fuzzy Matching and Evidential Reasoning.- Modeling Positive and Negative Pieces of Evidence in Uncertainty.- Directed Evidential Networks with Conditional Belief Functions.- Computational-Workload Based Binarization and Partition of Qualitative Markov Trees for Belief Combination.- Risk Assessment in Drinking WaterProduction Using Belief Functions.- Algebraic Structures Related to the Consensus Operator for Combining of Beliefs.- Fuzzy Sets.- Inclusion Measures in Intuitionistic Fuzzy Set Theory.- A Random Set Model for Fuzzy Labels.- On the Induction of Different Kinds of First-Order Fuzzy Rules.- Reasoning under Vagueness Expressed by Nuanced Statements.- Possibility Theory.- Partial Lattice-Valued Possibilistic Measures and Some Relations Induced by Them.- Coherent Conditional Probability as a Measure of Uncertainty of the Relevant Conditioning Events.- Decision Trees and Qualitative Possibilistic Inference: Application to the Intrusion Detection Problem.- Default Reasoning.- Multi-valued Conditional Events Avoid Lewis’ Triviality Result.- Solving Semantic Problems with Odd-Length Cycles in Argumentation.- On the Relation between Reiter’s Default Logic and Its (Major) Variants.- Belief Revision and Inconsistency Handling.- Probable Consistency Checking for Sets of Propositional Clauses.- On Iterated Revision in the AGM Framework.- Epistemic Logics for Information Fusion.- Logics.- Propositional Fusion Rules.- Preferential Logics for Reasoning with Graded Uncertainty.- Paraconsistent Reasoning via Quantified Boolean Formulas, II: Circumscribing Inconsistent Theories.- Modal (Logic) Paraconsistency.- A Formal Framework for Handling Conflicting Desires.- A Sequent Calculus for Skeptical Reasoning in Predicate Default Logic (Extended Abstract).- Probabilistic Lexicographic Entailment under Variable-Strength Inheritance with Overriding.- Demo Papers.- ABEL: An Interactive Tool for Probabilistic Argumentative Reasoning.- The Hugin Tool for Learning Bayesian Networks.