Title: Symbolic and quantitative approaches to reasoning with uncertainty
Description: Symbolic and Quantitative Approaches to Reasoning with Uncertainty: 6th European Conference, ECSQARU 2001 Toulouse, France, September 19–21, 2001 Proceedings<br />Author: Salem Benferhat, Philippe Besnard<br /> Published by Springer Berlin Heidelberg<br /> ISBN: 978-3-540-42464-2<br /> DOI: 10.1007/3-540-44652-4<br /><br />Table of Contents:<p></p><ul><li>Graphical Models as Languages for Computer Assisted Diagnosis and Decision Making
</li><li>Planning with Uncertainty and Incomplete Information
</li><li>What’s Your Preference? And How to Express and Implement It in Logic Programming!
</li><li>On Preference Representation on an Ordinal Scale
</li><li>Rule-Based Decision Support in Multicriteria Choice and Ranking
</li><li>Propositional Distances and Preference Representation
</li><li>Value Iteration over Belief Subspace
</li><li>Space-Progressive Value Iteration: An Anytime Algorithm for a Class of POMDPs
</li><li>Reasoning about Intentions in Uncertain Domains
</li><li>Troubleshooting with Simultaneous Models
</li><li>A Rational Conditional Utility Model in a Coherent Framework
</li><li>Probabilistic Reasoning as a General Unifying Tool
</li><li>An Operational View of Coherent Conditional Previsions
</li><li>Decomposition of Influence Diagrams
</li><li>Mixtures of Truncated Exponentials in Hybrid Bayesian Networks
</li><li>Importance Sampling in Bayesian Networks Using Antithetic Variables
</li><li>Using Recursive Decomposition to Construct Elimination Orders, Jointrees, and Dtrees
</li><li>Caveats For Causal Reasoning With Equilibrium Models
</li><li>Supporting Changes in Structure in Causal Model Construction
</li><li>The Search of Causal Orderings: A Short Cut for Learning Belief Networks</li></ul>
Subjects: Uncertainty (Information theory), Congresses, Reasoning, Artificial intelligence, Uncertainty (information theory)