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Books on the topic 'Constraint satisfaction'

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Published: 4 June 2021
Last updated: 29 July 2024

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1

Ghédira, Khaled, and Bernard Dubuisson, eds. Constraint Satisfaction Problems. Hoboken, NJ USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118574522.

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2

Yokoo, Makoto. Distributed Constraint Satisfaction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-59546-2.

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3

Tsang, Edward. Foundations of constraint satisfaction. Colchester: The author, 1996.

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4

Jermann, Christophe, Arnold Neumaier, and Djamila Sam, eds. Global Optimization and Constraint Satisfaction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b136292.

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5

Bliek, Christian, Christophe Jermann, and Arnold Neumaier, eds. Global Optimization and Constraint Satisfaction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/b94062.

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6

Hentenryck, Pascal Van. Constraint satisfaction in logic programming. Cambridge, Mass: MIT Press, 1989.

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7

Petke, Justyna. Bridging Constraint Satisfaction and Boolean Satisfiability. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21810-6.

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8

Hyafil, Nathanael. Probabilistic planning with constraint satisfaction techniques. Ottawa: National Library of Canada, 2003.

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9

Güsgen, Hans Werner. CONSAT: A system for constraint satisfaction. London: Pitman, 1989.

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10

Güsgen, Hans Werner. CONSAT: A system for constraint satisfaction. London: Pitman, 1989.

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11

Derthick, Mark. Mundane reasoning by parallel constraint satisfaction. London: Pitman, 1990.

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12

Beck, John Christopher. A schema for constraint relaxation with instantiations for partial constraints partial constraint satisfaction and schedule optimization. Ottawa: National Library of Canada, 1994.

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13

Živný, Stanislav. The Complexity of Valued Constraint Satisfaction Problems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33974-5.

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14

Creignou, Nadia. Complexity classifications of Boolean constraint satisfaction problems. Philadelphia: Society for Industrial and Applied Mathematics, 2001.

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15

Hjerpe, Torkel. High-level specification and efficient solving of constraint satisfaction problems. Uppsala: Computing Science Dept., Uppsala University, 1995.

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16

A. S. Janet van der Linden. Dynamic meta-constraints: An approach to dealing with non-standard constraint satisfaction problems. Oxford: Oxford Brookes University, 2000.

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17

Beck, John Christopher. A schema for constraint relaxation with instantiations for partial constraint satisfaction and schedule optimization. Toronto: University of Toronto, Dept. of Computer Science, 1994.

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18

Wahbi, Mohamed. Algorithms and Ordering Heuristics for Distributed Constraint Satisfaction Problems. Hoboken, NJ USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118753620.

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19

Wahbi, Mohamed. Algorithms and ordering heuristics for distributed constraint satisfaction problems. London, UK: ISTE, 2013.

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20

1963-, Bliek Christian, Jermann Christophe 1975-, and Neumaier A, eds. Global optimization and constraint satisfaction: First international workshop global constraint optimization and constraint satisfaction, COCOS 2002, Valbonne-Sophia Antipolis, France, October 2-4, 2002 : revised selected papers. Berlin: Springer-Verlag, 2003.

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21

1975-, Jermann Christophe, Neumaier A, and Sam Djamila, eds. Global optimization and constraint satisfaction: Second international workshop, COCOS 2003, Lausanne, Switzerland, November 18-21, 2003 : revised selected papers. Berlin: Springer, 2005.

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22

Miguel, Ian. Dynamic flexible constraint satisfaction and its application to AI planning. London: Springer, 2004.

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23

Miguel, Ian. Dynamic Flexible Constraint Satisfaction and its Application to AI Planning. London: Springer London, 2004. http://dx.doi.org/10.1007/978-0-85729-378-7.

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24

Miguel, Ian. Dynamic Flexible Constraint Satisfaction and its Application to AI Planning. London: Springer London, 2004.

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25

Yokoo, Makoto. Distributed Constraint Satisfaction: Foundations of Cooperation in Multi-agent Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001.

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26

Kubica, Bartłomiej Jacek. Interval Methods for Solving Nonlinear Constraint Satisfaction, Optimization and Similar Problems. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13795-3.

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27

Nachtsheim, Philip R. A technique for solving constraint satisfaction problems using Prolog's definite clause grammars. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1989.

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28

Steven, Minton, and Ames Research Center. Artificial Intelligence Research Branch., eds. Minimizing conflicts: A heuristic repair model for constraint-satisfaction and scheduling problems. [Moffett Field, Calif.]: NASA, Ames Research Center, Artificial Intelligence Research Branch, 1992.

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29

Steven, Minton, and Ames Research Center. Artificial Intelligence Research Branch., eds. Minimizing conflicts: A heuristic repair model for constraint-satisfaction and scheduling problems. [Moffett Field, Calif.]: NASA, Ames Research Center, Artificial Intelligence Research Branch, 1992.

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30

Timmer, Adwin H. From design space exploration to code generation: A constraint satisfaction approach for the architectural synthesis of digital VLSI circuits : proefschrift / door Adwin H. Timmer. [S.l: s.n.,], 1996.

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31

Distributed Constraint Satisfaction. Island Press, 2000.

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32

Foundations of Constraint Satisfaction. Elsevier, 1993. http://dx.doi.org/10.1016/c2013-0-07627-x.

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33

Foundations of Constraint Satisfaction. Books on Demand GmbH, 2014.

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34

Golan, Amos. Causal Inference via Constraint Satisfaction. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199349524.003.0011.

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Abstract:
In this chapter I introduce a number of ideas connected to causal inference that are inherently connected to info-metrics. In the context of this chapter, causal inference means the causality inferred from the available information. I begin by introducing and examining nonmonotonic and default logics, which were developed to deal with extremely high conditional probabilities. Other facets of info-metrics and causal inference are then discussed. I also show the direct effect of the complete set of input information on the inferred solution. I conclude the chapter with a detailed Markov example providing a more traditional approach to causal inference, developed within the info-metrics framework. The example builds on the notion of exogeneity and demonstrates that the info-metrics framework provides a simple way of incorporating additional exogenous information, thereby opening the way for empirical testing of causal inference. A short summary of the notion of “pure” causality is also provided.
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35

Arnold Neumaier,Christophe Jermann,Djamila Sam. Global Optimization and Constraint Satisfaction. Springer, 2008.

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36

Constraint satisfaction-aided plan recognition. 2009.

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37

Petke, Justyna. Bridging Constraint Satisfaction and Boolean Satisfiability. Springer, 2015.

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38

Bodirsky, Manuel. Complexity of Infinite-Domain Constraint Satisfaction. University of Cambridge ESOL Examinations, 2021.

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39

Petke, Justyna. Bridging Constraint Satisfaction and Boolean Satisfiability. Springer, 2015.

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40

Bodirsky, Manuel. Complexity of Infinite-Domain Constraint Satisfaction. University of Cambridge ESOL Examinations, 2021.

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41

ivný, Stanislav. Complexity of Valued Constraint Satisfaction Problems. Springer, 2014.

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42

Mitchell, David Geoffrey. The resolution complexity of constraint satisfaction. 2002.

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43

Petke, Justyna. Bridging Constraint Satisfaction and Boolean Satisfiability. Springer, 2016.

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44

Neagu, Nicoleta. Constraint Satisfaction Techniques for Agent-Based Reasoning. Birkhauser Verlag, 2007.

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45

Ghedira, Khaled. Constraint Satisfaction Problems: CSP Formalisms and Techniques. Wiley & Sons, Incorporated, John, 2013.

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46

Zivný, Stanislav. The Complexity of Valued Constraint Satisfaction Problems. Springer, 2012.

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47

Ghedira, Khaled. Constraint Satisfaction Problems: CSP Formalisms and Techniques. Wiley & Sons, Limited, John, 2013.

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48

Constraint Satisfaction Techniques for Agent-Based Reasoning. Basel: Birkhäuser-Verlag, 2005. http://dx.doi.org/10.1007/b137139.

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49

Ghedira, Khaled. Constraint Satisfaction Problems: CSP Formalisms and Techniques. Wiley & Sons, Incorporated, John, 2013.

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50

Cambridge, University of, ed. Constraint specification and satisfaction in embodiment design. 1993.

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