Symbolic and Quantitative Approaches to Reasoning and Uncertainty (eBook, PDF)

European Conference, ECSQARU'99, London, UK, July 5-9, 1999, Proceedings
Redaktion: Hunter, Anthony; Parsons, Simon D.

• Format: PDF

Produktbeschreibung

This book constitutes the refereed proceedings of the 1999 European Conference on Symbolic and Quantitative Approaches to Reasoning under Uncertainty, ECSQARU'99, held in London, UK, in July 1999.The 35 revised full papers presented were carefully reviewed and selected for inclusion in the book by the program committee. The volume covers theoretical as well as application-oriented aspects of various formalisms for reasoning under uncertainty. Among the issues addressed are default reasoning, nonmonotonic reasoning, fuzzy logic, Bayesian theory, probabilistic reasoning, inductive learning, rough knowledge discovery, Dempster-Shafer theory, qualitative decision making, belief functions, and evidence theory.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 402
• Erscheinungstermin: 15. Mai 2003
• Englisch
• ISBN-13: 9783540487470
• Artikelnr.: 53146868

Inhaltsangabe

On the Dynamics of Default Reasoning.- Nonmonotonic and Paraconsistent Reasoning: From Basic Entailments to Plausible Relations.- A Comparison of Systematic and Local Search Algorithms for Regular CNF Formulas.- Query-answering in Prioritized Default Logic.- Updating Directed Belief Networks.- Inferring Causal Explanations.- A Critique of Inductive Causation.- Connecting Lexicographic with Maximum Entropy Entailment.- Avoiding Non-Ground Variables.- Anchoring Symbols to Vision Data by Fuzzy Logic.- Filtering vs Revision and Update: let us Debate!.- Irrelevance and Independence Axioms in Quasi-Bayesian Theory.- Assessing the value of a candidate.- Learning Default Theories.- Knowledge Representation for Inductive Learning.- Handling Inconsistency Efficiently in the Incremental Construction of Stratified Belief Bases.- Rough Knowledge Discovery and Applications.- Gradient Descent Training of Bayesian Networks.- Open Default Theories over Closed Domains.- Shopbot Economics.- Optimized Algorithm for Learning Bayesian Network from Data.- Merging with Integrity Constraints.- Boolean-like Interpretation of Sugeno Integral.- An Alternative to Outward Propagation for Dempster-Shafer Belief Functions.- On bottom-up pre-processing techniques for automated default reasoning.- Probabilisitc Logic Programming under Maximum Entropy.- Lazy Propagation and Independence of Causal Influence.- A Monte Carlo Algorithm for Combining Dempster-Shafer Belief Based on Approximate Pre-Computation.- An Extension of a lInguistic Negation Model allowing us to Deny Nuanced Property Combinations.- Argumentation and Qualitative Decision Making.- Handling Different Forms of Uncertainty in Regression Analysis: A Fuzzy Belief Structure Approach.- State Recognition in Discrete Dynamical Systems using PetriNets and Evidence Theory.- Robot Navigation and Map Building with the Event Calculus.- Information Fusion in the Context of Stock Index Prediction.- Defeasible Goals.- Logical Deduction using the Local Computation Framework.