By Francesca Rossi, Peter van Beek, Toby Walsh
Instruction manual of Constraint ProgrammingEdited byFrancesca Rossi, college of Padova, ItalyPeter van Beek, college of Waterloo, CanadaToby Walsh, nationwide ICT Australia & college of recent South Wales, Australia"This encyclopedic paintings covers twenty-plus years of study in constraint programming in a readable, available and attractive approach. for somebody outdoors the sphere pondering what Constraint Programming is all approximately, this is often the right advent, and the booklet will stay invaluable as a reference for years.- Michael Trick, Professor of Operations learn, Tepper college of industrial, Carnegie Mellon University"This ebook is a powerful and complete insurance of Constraint Programming. The authors, a lot of whom are key participants to the themes defined, have performed a good task to make the real and fascinating fabric obtainable. A must-read for newbies, and vital for the converts.- Joxan Jaffar, Professor and Dean, tuition of Computing, nationwide college of Singapore"This guide captures the breadth and class of the sphere of constraint programming (CP), a swiftly transforming into quarter of study with major educational and advertisement influence. The editors and individuals supply an excellent assessment of the middle and leading edge recommendations within the box. This instruction manual can be necessary to all CP researchers and practitioners. it is going to even be an excellent consultant for researchers from similar fields, akin to optimization and operations research.- Bart Selman, Professor of machine technology, Cornell UniversityConstraint programming is a robust paradigm for fixing combinatorial andnumerical difficulties that attracts on a variety of options from man made intelligence, desktop technology, databases, programming languages, and operations study. Constraint programming is presently utilized with luck to many domain names, corresponding to scheduling, making plans, automobile routing, configuration, networks, and bioinformatics.The goal of this guide is to trap the entire breadth and intensity of the sphere of constraint programming and to be encyclopedic in its scope and assurance. each one bankruptcy of the guide is a self-contained survey of a subject matter, and is written via a number of authors who're major researchers within the area.The meant viewers of the instruction manual is researchers, graduate scholars, upper-year undergraduates, and practitioners who desire to know about the state of the art in constraint programming. No past wisdom concerning the box is important with a purpose to learn the chapters and assemble worthy wisdom. Researchers from different fields will locate the instruction manual a great way to profit approximately constraint programming and which will use constraint programming techniques and strategies of their personal paintings.
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Extra resources for Handbook of Constraint Programming
Waltz. Understanding line drawings of scenes with shadows. In P. H. Winston, editor, The Psychology of Computer Vision, pages 19–91. McGraw-Hill, 1975.  M. V. Wilkes. Constraint-type statements in programming languages. CACM, 7(10): 587–588, 1964. 364967. This page intentionally left blank Handbook of Constraint Programming Edited by F. Rossi, P. van Beek and T. V. All rights reserved 29 Chapter 3 Constraint Propagation Christian Bessiere Constraint propagation is a form of inference, not search, and as such is more ”satisfying”, both technically and aesthetically.
ACM Press. ISBN 0-89791-570-4. M. Davis and H. Putnam. A computing procedure for quantification theory. J. ACM, 7:201–215, 1960. M. Davis, G. Logemann, and D. Loveland. A machine program for theorem-proving. Comm. ACM, 5:394–397, 1962. J. de Kleer. Local methods for localizing faults in electronic circuits. Technical Report AIM-394, MIT Artificial Intelligence Laboratory, Nov. 6 1976. 1/6921. J. de Kleer and G. J. Sussman. Propagation of constraints applied to circuit synthesis. Technical Report AIM-485, MIT Artificial Intelligence Laboratory, Sept.
53] A. K. Mackworth. Consistency in networks of relations. Artificial Intelligence, 8: 99–118, 1977.  A. K. Mackworth. The logic of constraint satisfaction. Artificial Intelligence, 58: 3–20, 1992.  A. K. Mackworth and E. C. Freuder. The complexity of some polynomial network consistency algorithms for constraint satisfaction problems. Artificial Intelligence, 25:65–74, 247, 1985.  A. K. Mackworth and E. C. Freuder. The complexity of constraint satisfaction revisited. Artificial Intelligence, 59:57–62, 1993.