Authors:
- Explains why SAT-solvers are efficient on certain classes of CSPs
- Explains which SAT encodings preserve tractability of certain classes of CSPs
- Valuable for researchers and graduate students in artificial intelligence and theoretical computer science
- Includes supplementary material: sn.pub/extras
Part of the book series: Artificial Intelligence: Foundations, Theory, and Algorithms (AIFTA)
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Table of contents (8 chapters)
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Front Matter
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Back Matter
About this book
This book provides a significant step towards bridging the areas of Boolean satisfiability and constraint satisfaction by answering the question why SAT-solvers are efficient on certain classes of CSP instances which are hard to solve for standard constraint solvers. The author also gives theoretical reasons for choosing a particular SAT encoding for several important classes of CSP instances.
Boolean satisfiability and constraint satisfaction emerged independently as new fields of computer science, and different solving techniques have become standard for problem solving in the two areas. Even though any propositional formula (SAT) can be viewed as an instance of the general constraint satisfaction problem (CSP), the implications of this connection have only been studied in the last few years.
The book will be useful for researchers and graduate students in artificial intelligence and theoretical computer science.Â
Authors and Affiliations
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Dept. of Computer Science, University College London, London, United Kingdom
Justyna Petke
About the author
Justyna Petke received her D.Phil. from the University of Oxford. She is a Research Associate at the Centre for Research on Evolution, Search and Testing (CREST) in the Dept. of Computer Science, University College London. Her research interests include the connections between constraint satisfaction and search-based software engineering, including genetic improvement and combinatorial interaction testing.
Bibliographic Information
Book Title: Bridging Constraint Satisfaction and Boolean Satisfiability
Authors: Justyna Petke
Series Title: Artificial Intelligence: Foundations, Theory, and Algorithms
DOI: https://doi.org/10.1007/978-3-319-21810-6
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2015
Hardcover ISBN: 978-3-319-21809-0Published: 19 August 2015
Softcover ISBN: 978-3-319-37364-5Published: 22 October 2016
eBook ISBN: 978-3-319-21810-6Published: 25 August 2015
Series ISSN: 2365-3051
Series E-ISSN: 2365-306X
Edition Number: 1
Number of Pages: XI, 113
Number of Illustrations: 19 b/w illustrations