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  1. 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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  • Solving connected row convex constraints by variable elimination.Yuanlin Zhang & Satyanarayana Marisetti - 2009 - Artificial Intelligence 173 (12-13):1204-1219.
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  • Properties of tree convex constraints.Yuanlin Zhang & Eugene C. Freuder - 2008 - Artificial Intelligence 172 (12-13):1605-1612.
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  • Multi-agent path finding with mutex propagation.Han Zhang, Jiaoyang Li, Pavel Surynek, T. K. Satish Kumar & Sven Koenig - 2022 - Artificial Intelligence 311 (C):103766.
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  • A theory of conflict resolution in planning.Qiang Yang - 1992 - Artificial Intelligence 58 (1-3):361-392.
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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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  • Qualitative reasoning with directional relations.D. Wolter & J. H. Lee - 2010 - Artificial Intelligence 174 (18):1498-1507.
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  • Constraint-based reasoning and privacy/efficiency tradeoffs in multi-agent problem solving.Richard J. Wallace & Eugene C. Freuder - 2005 - Artificial Intelligence 161 (1-2):209-227.
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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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  • A gentle introduction to Numerica.Pascal Van Hentenryck - 1998 - Artificial Intelligence 103 (1-2):209-235.
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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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  • Investigating production system representations for non-combinatorial match.Milind Tambe & Paul S. Rosenbloom - 1994 - Artificial Intelligence 68 (1):155-199.
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  • Planning with constraints.Mark Stefik - 1981 - Artificial Intelligence 16 (2):111-139.
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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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  • Parsing as non-Horn deduction.Edward P. Stabler - 1993 - Artificial Intelligence 63 (1-2):225-264.
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  • Asynchronous aggregation and consistency in distributed constraint satisfaction.Marius-Călin Silaghi & Boi Faltings - 2005 - Artificial Intelligence 161 (1-2):25-53.
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  • The increasing cost tree search for optimal multi-agent pathfinding.Guni Sharon, Roni Stern, Meir Goldenberg & Ariel Felner - 2013 - Artificial Intelligence 195 (C):470-495.
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  • A Probabilistic Constraints Approach to Language Acquisition and Processing.Mark S. Seidenberg & Maryellen C. MacDonald - 1999 - Cognitive Science 23 (4):569-588.
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  • Spatial relation learning for explainable image classification and annotation in critical applications.Régis Pierrard, Jean-Philippe Poli & Céline Hudelot - 2021 - Artificial Intelligence 292 (C):103434.
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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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  • Arc consistency for factorable relations.Mark Perlin - 1992 - Artificial Intelligence 53 (2-3):329-342.
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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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  • Constraint propagation as information maximization.A. Nait Abdallah & M. H. van Emden - 2013 - Artificial Intelligence 197 (C):25-38.
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  • Qualitative reasoning about relative direction of oriented points.Till Mossakowski & Reinhard Moratz - 2012 - Artificial Intelligence 180-181 (C):34-45.
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  • A condensed semantics for qualitative spatial reasoning about oriented straight line segments.Reinhard Moratz, Dominik Lücke & Till Mossakowski - 2011 - Artificial Intelligence 175 (16-17):2099-2127.
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  • Constraint relaxation may be perfect.Ugo Montanari & Francesca Rossi - 1991 - Artificial Intelligence 48 (2):143-170.
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  • Arc and path consistency revisited.Roger Mohr & Thomas C. Henderson - 1986 - Artificial Intelligence 28 (2):225-233.
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  • Fuzzy rrDFCSP and planning.Ian Miguel & Qiang Shen - 2003 - Artificial Intelligence 148 (1-2):11-52.
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  • Combining qualitative and quantitative constraints in temporal reasoning.Itay Meiri - 1996 - Artificial Intelligence 87 (1-2):343-385.
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  • The logic of constraint satisfaction.Alan K. Mackworth - 1992 - Artificial Intelligence 58 (1-3):3-20.
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  • The complexity of constraint satisfaction revisited.Alan K. Mackworth & Eugene C. Freuder - 1993 - Artificial Intelligence 59 (1-2):57-62.
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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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  • A fuzzy constraint based model for bilateral, multi-issue negotiations in semi-competitive environments.Xudong Luo, Nicholas R. Jennings, Nigel Shadbolt, Ho-Fung Leung & Jimmy Ho-man Lee - 2003 - Artificial Intelligence 148 (1-2):53-102.
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  • A spectrum of compromise aggregation operators for multi-attribute decision making.Xudong Luo & Nicholas R. Jennings - 2007 - Artificial Intelligence 171 (2-3):161-184.
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  • Variable-Centered Consistency in Model RB.Liang Li, Tian Liu & Ke Xu - 2013 - Minds and Machines 23 (1):95-103.
    Model RB is a model of random constraint satisfaction problems, which exhibits exact satisfiability phase transition and many hard instances, both experimentally and theoretically. Benchmarks based on Model RB have been successfully used by various international algorithm competitions and many research papers. In a previous work, Xu and Li defined two notions called i-constraint assignment tuple and flawed i-constraint assignment tuple to show an exponential resolution complexity of Model RB. These two notions are similar to some kind of consistency in (...)
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  • Multi-agent oriented constraint satisfaction.Jiming Liu, Han Jing & Y. Y. Tang - 2002 - Artificial Intelligence 136 (1):101-144.
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  • Logic and AI in China: An Introduction. [REVIEW]Fenrong Liu & Kaile Su - 2013 - Minds and Machines 23 (1):1-4.
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  • A probabilistic approach to solving crossword puzzles.Michael L. Littman, Greg A. Keim & Noam Shazeer - 2002 - Artificial Intelligence 134 (1-2):23-55.
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  • Planning parallel actions.A. R. Lingard & E. B. Richards - 1998 - Artificial Intelligence 99 (2):261-324.
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  • Towards breaking more composition symmetries in partial symmetry breaking.Jimmy H. M. Lee & Zichen Zhu - 2017 - Artificial Intelligence 252 (C):51-82.
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  • Problem solving by searching for models with a theorem prover.Shie-Jue Lee & David A. Plaisted - 1994 - Artificial Intelligence 69 (1-2):205-233.
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  • Automatic generation of dominance breaking nogoods for a class of constraint optimization problems.Jimmy H. M. Lee & Allen Z. Zhong - 2023 - Artificial Intelligence 323 (C):103974.
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  • STR3: A path-optimal filtering algorithm for table constraints.Christophe Lecoutre, Chavalit Likitvivatanavong & Roland H. C. Yap - 2015 - Artificial Intelligence 220 (C):1-27.
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  • Accelerating filtering techniques for numeric CSPs.Yahia Lebbah & Olivier Lhomme - 2002 - Artificial Intelligence 139 (1):109-132.
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  • Solving weighted CSP by maintaining arc consistency.Javier Larrosa & Thomas Schiex - 2004 - Artificial Intelligence 159 (1-2):1-26.
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  • Localized planning with action-based constraints.Amy L. Lansky - 1998 - Artificial Intelligence 98 (1-2):49-136.
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  • Effective solution of qualitative interval constraint problems.Peter B. Ladkin & Alexander Reinefeld - 1992 - Artificial Intelligence 57 (1):105-124.
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