Symbolic and Quantitative Approaches to Reasoning and Uncertainty European Conference, ECSQARU'99, London, UK, July 5-9, 1999, Proceedings
Other Authors: | , |
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Format: | eBook |
Language: | English |
Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
1999, 1999
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Edition: | 1st ed. 1999 |
Series: | Lecture Notes in Artificial Intelligence
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Subjects: | |
Online Access: | |
Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- 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
- 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