Symbolic and Quantitative Approaches to Reasoning and Uncertainty: European Conference, ECSQARU'99, London, UK, July 5-9, 1999, Proceedings: Lecture Notes in Computer Science, cartea 1638

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.

Includes supplementary material: sn.pub/extras