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  1. Filtering algorithms for the multiset ordering constraint.Alan M. Frisch, Brahim Hnich, Zeynep Kiziltan, Ian Miguel & Toby Walsh - 2009 - Artificial Intelligence 173 (2):299-328.
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  • The complexity of some polynomial network consistency algorithms for constraint satisfaction problems.Alan K. Mackworth & Eugene C. Freuder - 1985 - Artificial Intelligence 25 (1):65-74.
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  • Learning to improve constraint-based scheduling.Monte Zweben, Eugene Davis, Brian Daun, Ellen Drascher, Michael Deale & Megan Eskey - 1992 - Artificial Intelligence 58 (1-3):271-296.
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  • Arc-consistency and arc-consistency again.Christian Bessière - 1994 - Artificial Intelligence 65 (1):179-190.
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  • Locating the phase transition in binary constraint satisfaction problems.Barbara M. Smith & Martin E. Dyer - 1996 - Artificial Intelligence 81 (1-2):155-181.
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  • Backtracking algorithms for disjunctions of temporal constraints.Kostas Stergiou & Manolis Koubarakis - 2000 - Artificial Intelligence 120 (1):81-117.
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  • Random constraint satisfaction: Easy generation of hard (satisfiable) instances.Ke Xu, Frédéric Boussemart, Fred Hemery & Christophe Lecoutre - 2007 - Artificial Intelligence 171 (8-9):514-534.
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  • Reasoning about qualitative temporal information.Peter van Beek - 1992 - Artificial Intelligence 58 (1-3):297-326.
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  • Constraint satisfaction using constraint logic programming.Pascal Van Hentenryck, Helmut Simonis & Mehmet Dincbas - 1992 - Artificial Intelligence 58 (1-3):113-159.
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  • A generic arc-consistency algorithm and its specializations.Pascal Van Hentenryck, Yves Deville & Choh-Man Teng - 1992 - Artificial Intelligence 57 (2-3):291-321.
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  • No more “Partial” and “Full Looking Ahead”.Edward Tsang - 1998 - Artificial Intelligence 98 (1-2):351-361.
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  • Determining if (FC-) (conflict-directed) backjumping visits a given node is NP-hard.Bernd S. W. Schröder - 2001 - Artificial Intelligence 132 (1):105-117.
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  • Variable and value ordering heuristics for the job shop scheduling constraint satisfaction problem.Norman Sadeh & Mark S. Fox - 1996 - Artificial Intelligence 86 (1):1-41.
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  • Backtracking techniques for the job shop scheduling constraint satisfaction problem.Norman Sadeh, Katia Sycara & Yalin Xiong - 1995 - Artificial Intelligence 76 (1-2):455-480.
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  • An empirical study of phase transitions in binary constraint satisfaction problems.Patrick Prosser - 1996 - Artificial Intelligence 81 (1-2):81-109.
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  • Modelling and solving temporal reasoning as propositional satisfiability.Duc Nghia Pham, John Thornton & Abdul Sattar - 2008 - Artificial Intelligence 172 (15):1752-1782.
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  • Consistent-labeling problems and their algorithms: Expected-complexities and theory-based heuristics.Bernard Nudel - 1983 - Artificial Intelligence 21 (1-2):135-178.
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  • On the modelling and optimization of preferences in constraint-based temporal reasoning.Michael D. Moffitt - 2011 - Artificial Intelligence 175 (7-8):1390-1409.
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  • Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems.Steven Minton, Mark D. Johnston, Andrew B. Philips & Philip Laird - 1992 - Artificial Intelligence 58 (1-3):161-205.
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  • Fuzzy rrDFCSP and planning.Ian Miguel & Qiang Shen - 2003 - Artificial Intelligence 148 (1-2):11-52.
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  • Exploiting symmetries within constraint satisfaction search☆☆This paper is an extended and updated version of [16], presented at the IJCAI-99 conference. [REVIEW]Pedro Meseguer & Carme Torras - 2001 - Artificial Intelligence 129 (1-2):133-163.
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  • Reordering all agents in asynchronous backtracking for distributed constraint satisfaction problems.Younes Mechqrane, Mohamed Wahbi, Christian Bessiere & Kenneth N. Brown - 2020 - Artificial Intelligence 278 (C):103169.
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  • AND/OR Branch-and-Bound search for combinatorial optimization in graphical models.Radu Marinescu & Rina Dechter - 2009 - Artificial Intelligence 173 (16-17):1457-1491.
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  • Reasoning from last conflict(s) in constraint programming.Christophe Lecoutre, Lakhdar Saïs, Sébastien Tabary & Vincent Vidal - 2009 - Artificial Intelligence 173 (18):1592-1614.
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  • A theoretical evaluation of selected backtracking algorithms.Grzegorz Kondrak & Peter van Beek - 1997 - Artificial Intelligence 89 (1-2):365-387.
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  • Hybrid backtracking bounded by tree-decomposition of constraint networks.Philippe Jégou & Cyril Terrioux - 2003 - Artificial Intelligence 146 (1):43-75.
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  • The combinatorics of object recognition in cluttered environments using constrained search.W. Eric L. Grimson - 1990 - Artificial Intelligence 44 (1-2):121-165.
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  • Solving quantified constraint satisfaction problems.Ian P. Gent, Peter Nightingale, Andrew Rowley & Kostas Stergiou - 2008 - Artificial Intelligence 172 (6-7):738-771.
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  • Partial constraint satisfaction.Eugene C. Freuder & Richard J. Wallace - 1992 - Artificial Intelligence 58 (1-3):21-70.
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  • Efficient graph automorphism by vertex partitioning.Glenn Fowler, Robert Haralick, F. Gail Gray, Charles Feustel & Charles Grinstead - 1983 - Artificial Intelligence 21 (1-2):245-269.
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  • Semantic-based regularization for learning and inference.Michelangelo Diligenti, Marco Gori & Claudio Saccà - 2017 - Artificial Intelligence 244 (C):143-165.
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  • Temporal constraint networks.Rina Dechter, Itay Meiri & Judea Pearl - 1991 - Artificial Intelligence 49 (1-3):61-95.
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  • Network-based heuristics for constraint-satisfaction problems.Rina Dechter & Judea Pearl - 1987 - Artificial Intelligence 34 (1):1-38.
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  • Experimental evaluation of preprocessing algorithms for constraint satisfaction problems.Rina Dechter & Itay Meiri - 1994 - Artificial Intelligence 68 (2):211-241.
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  • Enhancement schemes for constraint processing: Backjumping, learning, and cutset decomposition.Rina Dechter - 1990 - Artificial Intelligence 41 (3):273-312.
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  • Backjump-based backtracking for constraint satisfaction problems.Rina Dechter & Daniel Frost - 2002 - Artificial Intelligence 136 (2):147-188.
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  • On forward checking for non-binary constraint satisfaction.Christian Bessière, Pedro Meseguer, Eugene C. Freuder & Javier Larrosa - 2002 - Artificial Intelligence 141 (1-2):205-224.
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  • Dynamic problem structure analysis as a basis for constraint-directed scheduling heuristics.J. Christopher Beck & Mark S. Fox - 2000 - Artificial Intelligence 117 (1):31-81.
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  • Binary vs. non-binary constraints☆☆This paper includes results that first appeared in [1,4,23]. This research has been supported in part by the Canadian Government through their NSERC and IRIS programs, and by the EPSRC Advanced Research Fellowship program. [REVIEW]Fahiem Bacchus, Xinguang Chen, Peter van Beek & Toby Walsh - 2002 - Artificial Intelligence 140 (1-2):1-37.
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