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Principles of constraint programming / (Record no. 6900)

MARC details
000 -LEADER
fixed length control field 07475cam a22003377i 4500
001 - CONTROL NUMBER
control field 13407524
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20201020131123.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 030513s2003 enka b 001 0 eng
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2003278560
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 0521825830 (hardback)
040 ## - CATALOGING SOURCE
Original cataloging agency UKM
Transcribing agency UKM
Modifying agency IXA
-- C#P
-- DLC
-- EG-NcFUE
Description conventions rda
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76.612
Item number .A68 2003
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.11
Edition number 21
Item number A.K.P
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Apt, Krzysztof R.,
Dates associated with a name 1949-
245 10 - TITLE STATEMENT
Title Principles of constraint programming /
Statement of responsibility, etc Krzysztof R. Apt.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Cambridge ;
-- New York :
Name of publisher, distributor, etc Cambridge University Press,
Date of publication, distribution, etc 2003.
300 ## - PHYSICAL DESCRIPTION
Extent xii, 407 p. :
Other physical details ill. ;
Dimensions 26 cm.
336 ## - CONTENT TYPE
Source rdacontent
Content type term text
337 ## - MEDIA TYPE
Source rdamedia
Media type term unmediated
338 ## - CARRIER TYPE
Source rdacarrier
Carrier type term volume
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references (p. 387-400) and indexes.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1 Introduction<br/>1.1 Basic characteristics of constraint programming<br/>1.2 Applications of constraint programming<br/>1.3 A very short history of the subject<br/>1.4 Our approach<br/>1.5 Organisation of the book<br/>2 Constraint satisfaction problems: examples<br/>2.1 Basic concepts<br/>2.2 Constraint satisfaction problems on integers<br/>2.3 Constraint satisfaction problems on reals<br/>2.4 Boolean constraint satisfaction problems<br/>2.5 Symbolic constraint satisfaction problems<br/>2.6 Constrained optimization problems<br/>2.7 Summary<br/>2.8 Exercises<br/>2.9 Bibliographic remarks<br/>2.10 References<br/>3 Constraint programming in a nutshell<br/>3.1 Equivalence of CSPs<br/>3.2 Basic framework for constraint programming<br/>3.2.1 PREPROCESS<br/>3.2.2 HAPPY<br/>3.2.3 ATOMIC<br/>3.2.4 SPLIT<br/>3.2.5 PROCEED BY CASES<br/>3.2.6 CONSTRAINT PROPAGATION<br/>3.2.7 Constraint propagation algorithms<br/>3.3 Example: Boolean constraints<br/>HAPPY<br/>ATOMIC<br/>SPLIT<br/>CONSTRAINT PROPAGATION<br/>PROCEED BY CASES<br/>3.4 Example: polynomial constraints on integer intervals<br/>PREPROCESS<br/>ATOMIC<br/>CONSTRAINT PROPAGATION<br/>SPLIT<br/>PROCEED BY CASES<br/>3.5 Summary<br/>3.6 Bibliographic remarks<br/>4 Some complete constraint solvers<br/>4.1 A proof theoretical framework<br/>4.1.1 Proof rules<br/>4.1.2 Derivations<br/>4.2 Term equations<br/>4.2.1 Terms<br/>4.2.2 Substitutions<br/>4.2.3 Unifiers and mgus<br/>4.2.4 Unification problem and solving of CSPs<br/>4.2.5 The UNIF proof system<br/>4.2.6 The MARTELLI–MONTANARI algorithm<br/>4.3 Linear equations over reals<br/>4.3.1 Linear expressions and linear equations<br/>4.3.2 Substitutions, unifiers and mgus<br/>4.3.3 Linear equations and CSPs<br/>4.3.4 The LIN proof system<br/>4.3.5 The GAUSS–JORDAN ELIMINATION algorithm<br/>4.3.6 The GAUSSIAN ELIMINATION algorithm<br/>4.4 Linear inequalities over reals<br/>4.4.1 Syntax<br/>4.4.2 Linear inequalities and CSPs<br/>4.4.3 The INEQ proof system<br/>4.4.4 The Fourier–Motzkin Elimination algorithm<br/>4.5 Summary<br/>4.6 Exercises<br/>4.7 Bibliographic remarks<br/>4.8 References<br/>5 Local consistency notions<br/>5.1 Node consistency<br/>5.2 Arc consistency<br/>5.3 Hyper-arc consistency<br/>5.4 Directional arc consistency<br/>5.5 Path consistency<br/>5.6 Directional path consistency<br/>5.7 k-consistency<br/>5.8 Strong k-consistency<br/>5.9 Relational consistency<br/>5.10 Graphs and CSPs<br/>5.11 Summary<br/>5.12 Exercises<br/>5.13 Bibliographic remarks<br/>5.14 References<br/>6 Some incomplete constraint solvers<br/>6.1 A useful lemma<br/>6.2 Equality and disequality constraints<br/>6.3 Boolean constraints<br/>6.3.1 Transformation rules<br/>6.3.2 Domain reduction rules<br/>6.3.3 Example: full adder circuit<br/>6.3.4 A characterisation of the system BOOL<br/>6.4 Linear constraints on integer intervals<br/>6.4.1 Domain reduction rules for inequality constraints<br/>6.4.2 Domain reduction rules for equality constraints<br/>6.4.4 Rules for strict inequality constraints<br/>6.4.5 Shifting from intervals to finite domains<br/>6.4.6 Example: the SEND + MORE = MONEY puzzle<br/>6.4.7 Bounds consistency<br/>6.4.8 A characterisation of the LINEAR EQUALITY rule<br/>6.5 Arithmetic constraints on integer intervals<br/>6.5.1 Domain reduction rules: first approach<br/>6.5.2 Domain reduction rules: second approach<br/>6.5.3 Domain reduction rules: third approach<br/>6.5.4 Implementation of the third approach<br/>6.5.5 Shifting from intervals to finite domains<br/>6.6 Arithmetic constraints on reals<br/>6.6.1 Interval arithmetic<br/>6.6.2 Domain reduction rules<br/>6.6.3 Implementation issues<br/>6.6.4 Using floating-point intervals<br/>6.6.5 Correctness and effciency issues<br/>6.7 Arithmetic equations over reals<br/>6.8 Summary<br/>6.9 Exercises<br/>6.10 Bibliographic remarks<br/>6.11 References<br/>7 Constraint propagation algorithms<br/>7.1 Generic iteration algorithms<br/>7.1.1 Iterations<br/>7.1.2 Algorithms for arbitrary partial orderings<br/>7.2 From partial orderings to CSPs<br/>7.3 A node consistency algorithm<br/>7.4 An arc consistency algorithm<br/>7.5 A hyper-arc consistency algorithm<br/>7.6 A directional arc consistency algorithm<br/>7.7 A path consistency algorithm<br/>7.8 A directional path consistency algorithm<br/>7.9 A k-consistency algorithm<br/>7.10 A relational consistency algorithm<br/>7.11 Implementations of incomplete constraint solvers<br/>7.12 Summary<br/>7.13 Exercises<br/>7.14 Bibliographic remarks<br/>7.15 References<br/>8 Search<br/>8.1 Search trees<br/>8.2 Labeling trees<br/>8.2.1 Complete labeling trees<br/>8.2.2 Reduced labeling trees<br/>8.2.3 prop labeling trees<br/>8.3 An example: SEND + MORE = MONEY<br/>8.4 Instances of prop labeling trees<br/>8.4.1 Forward checking<br/>8.4.2 Partial look ahead<br/>8.4.3 Maintaining arc consistency (MAC)<br/>8.5 Search algorithms for the labeling trees<br/>8.5.1 Backtrack-free search<br/>8.5.2 Backtrack-free search with constraint propagation<br/>8.5.3 Backtracking<br/>8.5.4 Backtracking with constraint propagation<br/>8.6 Instances of backtracking with constraint propagation<br/>8.6.1 Forward checking<br/>8.6.2 Partial look ahead<br/>8.6.3 Maintaining arc consistency (MAC)<br/>8.6.4 Searching for all solutions<br/>8.7 Search algorithms for finite constrained optimization problems<br/>8.7.1 Branch and bound<br/>8.7.2 Branch and bound with constraint propagation<br/>8.7.3 Branch and bound with constraint propagation and cost constraint<br/>8.8 Heuristics for search algorithms<br/>8.8.1 Variable selection<br/>8.8.2 Value selection<br/>8.9 An abstract branch and bound algorithm<br/>8.10 Summary<br/>8.11 Exercises<br/>8.12 Bibliographic remarks<br/>8.13 References<br/>9 Issues in constraint programming<br/>9.1 Modeling<br/>9.1.1 Choosing the right variables<br/>9.1.2 Choosing the right constraints<br/>9.1.3 Choosing the right representation<br/>9.1.4 Global constraints<br/>9.2 Constraint programming languages<br/>9.2.1 Constraint logic programming<br/>9.2.2 ILOG solver<br/>9.2.3 Generation of constraints<br/>9.3 Constraint propagation<br/>9.4 Constraint solvers<br/>9.4.1 Building constraint solvers<br/>9.4.2 Incrementality<br/>9.4.3 Simplification of constraints<br/>9.5 Search<br/>9.5.1 Search in modeling languages<br/>9.5.2 Depth-first search: backtracking and branch and bound<br/>9.5.3 Breadth-first search and limited discrepancy search<br/>9.5.4 Local search<br/>9.5.5 Search in constraint programming languages<br/>9.5.6 Biology-inspired approaches<br/>9.6 Over-constrained problems<br/>9.6.1 Partial, weighted and fuzzy CSPs<br/>9.6.2 Constraint hierarchies<br/>9.6.3 Generalisations<br/>9.6.4 Reified constraints<br/>9.7 Summary<br/>9.8 Bibliographic remarks<br/>Bibliography<br/>Author index<br/>Subject index
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Constraint programming (Computer science)
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  Dewey Decimal Classification     Computers & Information Technology ( Computer Science ) Main library Main library A1 10/12/2012 MERIC 324.00 PU   005.11 A.K.P 00009218 18/02/2025 10/12/2012 Books