Abstraction, Reformulation, and Approximation
Subtitle: 4th International Symposium, SARA 2000 Horseshoe Bay, USA, July 26-29, 2000 Proceedings (Lecture Notes in Computer Science)
Contributors: Berthe Y. Choueiry (Editor); Toby Walsh (Editor)
Edition: 1 edition
Publisher: Springer
Published: August 17, 2000
Language: eng
Format: Paperback
Number of pages: 331
ISBN-13: 9783540678397
Subjects: Computer Programming; Computer Science (General); Computers; Computers - General Information; Science/Mathematics; Artificial Intelligence - General; General; Logic Design; Computers / Artificial Intelligence; Constraint programming; algorithmic learning; automated deduction; automatic programming; diagnosis; intelligent planning; Artificial Intelligence; Computer Science; Congresses
Description: Abstraction, Reformulation, and Approximation: 4th International Symposium, SARA 2000 Horseshoe Bay, USA, July 26–29, 2000 Proceedings<br />Author: Berthe Y. Choueiry, Toby Walsh<br /> Published by Springer Berlin Heidelberg<br /> ISBN: 978-3-540-67839-7<br /> DOI: 10.1007/3-540-44914-0<br /><br />Table of Contents:<p></p><ul><li>Partial Completeness of Abstract Fixpoint Checking
</li><li>An Overview of MAXQ Hierarchical Reinforcement Learning
</li><li>Recent Progress in the Design and Analysis of Admissible Heuristic Functions
</li><li>GIS Databases: From Multiscale to MultiRepresentation
</li><li>An Abstraction Framework for Soft Constraints and Its Relationship with Constraint Propagation
</li><li>Abstractions for Knowledge Organization of Relational Descriptions
</li><li>Grid-Based Histogram Arithmetic for the Probabilistic Analysis of Functions
</li><li>Approximating Data in Constraint Databases
</li><li>Linearly Bounded Reformulations of Unary Databases
</li><li>A CSP Abstraction Framework
</li><li>Interactions of Abstractions in Programming
</li><li>Reformulation and Approximation in Model Checking
</li><li>The Lumberjack Algorithm for Learning Linked Decision Forests
</li><li>Reformulating Propositional Satisfiability as Constraint Satisfaction
</li><li>Improving the Efficiency of Reasoning Through Structure-Based Reformulation
</li><li>Using Feature Hierarchies in Bayesian Network Learning
</li><li>On Reformulating Planning as Dynamic Constraint Satisfaction
</li><li>Experiments with Automatically Created Memory-Based Heuristics
</li><li>Abstraction and Phase Transitions in Relational Learning
</li><li>An Agent-Based Approach to Robust Switching Between Abstraction Levels for Fault Diagnosis</li></ul>