Symbolic and quantitative approaches to reasoning and uncertaintyEuropean conference, ECSQARU'99, London, UK, July 5-9, 1999 : proceedings
Guardat en:
| Autor corporatiu: | |
|---|---|
| Altres autors: | , |
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Col·lecció: | Lecture notes in computer science. Lecture notes in artificial intelligence
1638 |
| Matèries: | |
| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Symbolic and quantitative approaches to reasoning and uncertainty, European conference, ECSQARU'99, London, UK, July 5-9, 1999, proceedings, Anthony Hunter, Simon Parsons (Eds.), 1999, Berlin, Springer, 1 vol. (IX-396 p.), Lecture notes in computer science, 3-540-66131-X • Symbolic and Quantitative Approaches to Reasoning and Uncertainty, Texte imprimé, 9783662214794 |
Taula de continguts:
- 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.