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  1. Guarantees and limits of preprocessing in constraint satisfaction and reasoning.Serge Gaspers & Stefan Szeider - 2014 - Artificial Intelligence 216 (C):1-19.
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  • Constraint reasoning based on interval arithmetic: the tolerance propagation approach.Eero Hyvönen - 1992 - Artificial Intelligence 58 (1-3):71-112.
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  • Decomposing constraint satisfaction problems using database techniques.Marc Gyssens, Peter G. Jeavons & David A. Cohen - 1994 - Artificial Intelligence 66 (1):57-89.
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  • Fixed-parameter complexity in AI and nonmonotonic reasoning.Georg Gottlob, Francesco Scarcello & Martha Sideri - 2002 - Artificial Intelligence 138 (1-2):55-86.
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  • Compiling constraint satisfaction problems.Rainer Weigel & Boi Faltings - 1999 - Artificial Intelligence 115 (2):257-287.
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  • Diagnosing tree-structured systems☆☆Part of this work has been published in preliminary form in the Proceedings of the 15th International Joint Conference on Artificial Intelligence (IJCAI-97). [REVIEW]Markus Stumptner & Franz Wotawa - 2001 - Artificial Intelligence 127 (1):1-29.
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  • Coalition structure generation: A survey.Talal Rahwan, Tomasz P. Michalak, Michael Wooldridge & Nicholas R. Jennings - 2015 - Artificial Intelligence 229 (C):139-174.
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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 complexity of constraint satisfaction revisited.Alan K. Mackworth & Eugene C. Freuder - 1993 - Artificial Intelligence 59 (1-2):57-62.
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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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  • Unifying tree decompositions for reasoning in graphical models.Kalev Kask, Rina Dechter, Javier Larrosa & Avi Dechter - 2005 - Artificial Intelligence 166 (1-2):165-193.
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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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  • Domain permutation reduction for constraint satisfaction problems.Martin J. Green & David A. Cohen - 2008 - Artificial Intelligence 172 (8-9):1094-1118.
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  • A comparison of structural CSP decomposition methods.Georg Gottlob, Nicola Leone & Francesco Scarcello - 2000 - Artificial Intelligence 124 (2):243-282.
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  • Decomposable constraints☆☆Supported by EPSRC award GR/L/24014. The authors wish to thank other members of the APES research group.Ian Gent, Kostas Stergiou & Toby Walsh - 2000 - Artificial Intelligence 123 (1-2):133-156.
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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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  • Compiling propositional weighted bases.Adnan Darwiche & Pierre Marquis - 2004 - Artificial Intelligence 157 (1-2):81-113.
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  • Topological parameters for time-space tradeoff.Rina Dechter & Yousri El Fattah - 2001 - Artificial Intelligence 125 (1-2):93-118.
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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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  • Structure identification in relational data.Rina Dechter & Judea Pearl - 1992 - Artificial Intelligence 58 (1-3):237-270.
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  • Structure-driven algorithms for truth maintenance.Rina Dechter & Avi Dechter - 1996 - Artificial Intelligence 82 (1-2):1-20.
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  • From local to global consistency.Rina Dechter - 1992 - Artificial Intelligence 55 (1):87-107.
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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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  • AND/OR search spaces for graphical models.Rina Dechter & Robert Mateescu - 2007 - Artificial Intelligence 171 (2-3):73-106.
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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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  • Recursive conditioning.Adnan Darwiche - 2001 - Artificial Intelligence 126 (1-2):5-41.
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  • Generalizing constraint satisfaction on trees: Hybrid tractability and variable elimination.Martin C. Cooper, Peter G. Jeavons & András Z. Salamon - 2010 - Artificial Intelligence 174 (9-10):570-584.
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  • Default reasoning using classical logic.Rachel Ben-Eliyahu & Rina Dechter - 1996 - Artificial Intelligence 84 (1-2):113-150.
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  • A sufficiently fast algorithm for finding close to optimal clique trees.Ann Becker & Dan Geiger - 2001 - Artificial Intelligence 125 (1-2):3-17.
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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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  • Partition-based logical reasoning for first-order and propositional theories.Eyal Amir & Sheila McIlraith - 2005 - Artificial Intelligence 162 (1-2):49-88.
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  • Consistency restoration and explanations in dynamic CSPs—Application to configuration.Jérôme Amilhastre, Hélène Fargier & Pierre Marquis - 2002 - Artificial Intelligence 135 (1-2):199-234.
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