Academic literature on the topic 'Constraint Satisfaction Programming'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Constraint Satisfaction Programming.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Constraint Satisfaction Programming"
Van Hentenryck, Pascal, Helmut Simonis, and Mehmet Dincbas. "Constraint satisfaction using constraint logic programming." Artificial Intelligence 58, no. 1-3 (December 1992): 113–59. http://dx.doi.org/10.1016/0004-3702(92)90006-j.
Full textAPT, KRZYSZTOF R., and ERIC MONFROY. "Constraint programming viewed as rule-based programming." Theory and Practice of Logic Programming 1, no. 6 (November 2001): 713–50. http://dx.doi.org/10.1017/s1471068401000072.
Full textBooth, Kyle E. C., Bryan O'Gorman, Jeffrey Marshall, Stuart Hadfield, and Eleanor Rieffel. "Quantum-accelerated constraint programming." Quantum 5 (September 28, 2021): 550. http://dx.doi.org/10.22331/q-2021-09-28-550.
Full textRossi, Francesca, Kristen Brent Venable, and Toby Walsh. "Preferences in Constraint Satisfaction and Optimization." AI Magazine 29, no. 4 (December 28, 2008): 58. http://dx.doi.org/10.1609/aimag.v29i4.2202.
Full textRossi, Francesca. "Constraint satisfaction problems in logic programming." ACM SIGART Bulletin, no. 106 (October 1988): 24–28. http://dx.doi.org/10.1145/54350.54352.
Full textLEUNG, HO-FUNG, and KEITH L. CLARK. "Constraint Satisfaction in Distributed Concurrent Logic Programming." Journal of Symbolic Computation 21, no. 4-6 (April 1996): 699–714. http://dx.doi.org/10.1006/jsco.1996.0037.
Full textAlpuente, María, Moreno Falaschi, and Giorgio Levi. "Incremental constraint satisfaction for equational logic programming." Theoretical Computer Science 142, no. 1 (May 1995): 27–57. http://dx.doi.org/10.1016/0304-3975(94)00224-7.
Full textHo Geun Lee, Ronald M. Lee, and Gang Yu. "Constraint logic programming for qualitative and quantitative constraint satisfaction problems." Decision Support Systems 16, no. 1 (January 1996): 67–83. http://dx.doi.org/10.1016/0167-9236(94)00057-3.
Full textZHANG, YUANLIN, and ROLAND H. C. YAP. "Solving functional constraints by variable substitution." Theory and Practice of Logic Programming 11, no. 2-3 (February 4, 2011): 297–322. http://dx.doi.org/10.1017/s1471068410000591.
Full textLigęza, Antoni. "Models and Tools for Improving Efficiency in Constraint Logic Programming." Decision Making in Manufacturing and Services 5, no. 1 (October 3, 2011): 69–78. http://dx.doi.org/10.7494/dmms.2011.5.1.69.
Full textDissertations / Theses on the topic "Constraint Satisfaction Programming"
Nightingale, Peter. "Consistency and the quantified constraint satisfaction problem /." St Andrews, 2007. http://hdl.handle.net/10023/759.
Full textEgri, László. "The complexity of constraint satisfaction problems and symmetric Datalog /." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=101843.
Full textIn recent years, logical and algebraic perspectives have been particularly successful in classifying CSPs. A major weapon in the arsenal of the logical perspective is the database-theory-inspired logic programming language called Datalog. A Datalog program can be used to solve a restricted class of CSPs by either accepting or rejecting a (suitably encoded) set of input constraints. Inspired by Dalmau's work on linear Datalog and Reingold's breakthrough that undirected graph connectivity is in logarithmic space, we use a new restriction of Datalog called symmetric Datalog to identify a class of CSPs solvable in logarithmic space. We establish that expressibility in symmetric Datalog is equivalent to expressibility in a specific restriction of second order logic called Symmetric Restricted Krom Monotone SNP that has already received attention for its close relationship with logarithmic space.
We also give a combinatorial description of a large class of CSPs lying in L by showing that they are definable in symmetric Datalog. The main result of this thesis is that directed st-connectivity and a closely related CSP cannot be defined in symmetric Datalog. Because undirected st-connectivity can be defined in symmetric Datalog, this result also sheds new light on the computational differences between the undirected and directed st-connectivity problems.
Thornton, John. "Constraint Weighting Local Search for Constraint Satisfaction." Thesis, Griffith University, 2000. http://hdl.handle.net/10072/367954.
Full textThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Computing and Information Technology
Science, Environment, Engineering and Technology
Full Text
Thornton, John Richard, and n/a. "Constraint Weighting Local Search for Constraint Satisfaction." Griffith University. School of Computing and Information Technology, 2000. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20050901.142439.
Full textPadmanabhuni, Srinivas. "Logic programming with stable models for constraint satisfaction." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0009/NQ60011.pdf.
Full textZhang, Lixi. "Solving the timetabling problem using constraint satisfaction programming." Access electronically, 2005. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20051104.155838/index.html.
Full textThorstensen, Evgenij. "Hybrid tractability of constraint satisfaction problems with global constraints." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:05707b54-69e3-40eb-97e7-63b1a178c701.
Full textNightingale, Peter William. "Consistency and the Quantified Constraint Satisfaction Problem." Thesis, University of St Andrews, 2007. http://hdl.handle.net/10023/759.
Full textNilsson, Josefin. "Generating Playback Sequences of Songs with Constraint Satisfaction Programming." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279298.
Full textMed rätt låt vid rätt tidpunkt kan uppspelningssekvenser av låtar uppfylla de två grundläggande egenskaperna av en bra musiklyssningsupplevelse: önskan för upprepning och önskan för överraskningar. Många företag spelar musik kontinuerligt i sina lokaler med automatisk uppspelningsordning, och för dem kan en bra musikupplevelse förbättra den generella kundbelåtenheten samt öka försäljningen. Det här är något som Soundtrack Your Brand, ett musik- streamingföretag baserat i Stockholm, utnyttjar genom att erbjuda sina kunder musik skräddarsydd för deras företag. Ett sätt att generera uppspelningssekvenser av låtar givet en spellista och samtidigt definiera kriterier sekvensen ska uppfylla är genom att modellera det som ett villkorsproblem. Problemet kan definieras som att givet en spellista av låtar som indata, generera en uppspelningssekvens av låtar så att en mängd villkor över låtarna i sekvensens attribut är uppfyllda. Det här examensarbetet undersöker om Constraint Satisfaction Programming är en möjlig lösning för att generera uppspelningssekvenser och i så fall, hur effektivt det går att göra det. En Constraint Satisfaction Programming-sekvenserare implementeras som modellerar tre olika typer av villkor och an- vänder ett Hill Climbing-tillvägagångssätt för att lösa uppspelningsproblemet. Den föreslagna sekvenseraren jämförs med den nuvarande lösningen på Soundtrack Your Brand, som är en girig algoritm, samt en matematiskt slump- mässig blandning. Resultaten visar att den föreslagna lösningen presterar bättre än både den nuvarande lösningen och den slumpmässiga blandningen när det kommer till hur väl de uppfyller de definierade villkoren. Sekvenserarens effektivitets mäts med avseende på körtid om minnesanvändning i olika scenarion där resultaten indikerar bra prestanda när storleken på spellistan ökar. När den föreslagna sekvenseraren jämförs med den nuvarande lösningen har sekvenseraren kortare körtid för alla storlekar av spellistor som testades. Genom att kombinera resultaten av jämförelsen och effektivitetsutvärderingen slår det här examensarbetet fast att det är möjligt att generera uppspelningssekvenser med Constraint Satisfaction Programming och att det kan göras tillräckligt effektivt för att köras i en produktionsmiljö.
Gharbi, Nebras. "On compressing and parallelizing constraint satisfaction problems." Thesis, Artois, 2015. http://www.theses.fr/2015ARTO0406/document.
Full textConstraint Programming (CP) is a powerful paradigm used for modelling and solving combinatorial constraint problems that relies on a wide range of techniques coming from artificial intelligence, operational research, graph theory,..., etc. The basic idea of constraint programming is that the user expresses its constraints and a constraint solver seeks a solution. Constraint Satisfaction Problems (CSP), is a framework at the heart of CP problems. They correspond to decision problems where we seek for states or objects satisfying a number of constraints or criteria. These decision problems have two answers to the question they encode: true, if the problem admits a solution, false, otherwise. CSPs are the subject of intense research in both artificial intelligence and operations research. Many CSPs require the combination of heuristics and combinatorial optimization methods to solve them in a reasonable time.With the improvement of computers, larger and larger problems can be solved. However, the size of industrial problems grow faster which requires a vast amount of memory space to store them and entail great difficulties to solve them. In this thesis, our contributions can be divided into two main parts. In the first part, we deal with the most used kind of constraints, which are table constraints. We proposed two compressed forms of table constraints. Both of them are based on frequent patterns search in order to avoid redundancy. However, the manner of defining pattern, the patterns-detecting process and the new compact representation differ significantly. For each form, we propose a filtering algorithm. In the second part, we explore another way to optimize CSP solving which is the use of a parallel architecture. In fact, we enhance the solving process by establishing parallel consistencies. Different workers send to their master the result of establishing partial consistencies as new discovered facts. The master, in its turns tries to benefit from them by removing corresponding values
Books on the topic "Constraint Satisfaction Programming"
Hentenryck, Pascal Van. Constraint satisfaction in logic programming. Cambridge, Mass: MIT Press, 1989.
Find full textHjerpe, Torkel. High-level specification and efficient solving of constraint satisfaction problems. Uppsala: Computing Science Dept., Uppsala University, 1995.
Find full text1963-, 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.
Find full text1975-, 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.
Find full textWahbi, Mohamed. Algorithms and ordering heuristics for distributed constraint satisfaction problems. London, UK: ISTE, 2013.
Find full textMiguel, Ian. Dynamic flexible constraint satisfaction and its application to AI planning. London: Springer, 2004.
Find full textGlobal Optimization and Constraint Satisfaction: First International Workshop Global Constraint Optimization and Constraint Satisfaction, COCOS 2002, Valbonne-Sophia ... Papers (Lecture Notes in Computer Science). Springer, 2004.
Find full textWahbi, Mohamed. Algorithms and Ordering Heuristics for Distributed Constraint Satisfaction Problems. Wiley & Sons, Incorporated, John, 2013.
Find full textWahbi, Mohamed. Algorithms and Ordering Heuristics for Distributed Constraint Satisfaction Problems. Wiley & Sons, Incorporated, John, 2013.
Find full textWahbi, Mohamed. Algorithms and Ordering Heuristics for Distributed Constraint Satisfaction Problems. Wiley & Sons, Incorporated, John, 2013.
Find full textBook chapters on the topic "Constraint Satisfaction Programming"
Freuder, Eugene C. "Exploiting Structure in Constraint Satisfaction Problems." In Constraint Programming, 51–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85983-0_3.
Full textMayoh, Brian, Enn Tyugu, and Tarmo Uustalu. "Constraint Satisfaction and Constraint Programming: A Brief Lead-In." In Constraint Programming, 1–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85983-0_1.
Full textSolnon, Christine, and Narendra Jussien. "Constraint Satisfaction Problems." In Ant Colony Optimization and Constraint Programming, 31–52. Hoboken, NJ USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118557563.ch3.
Full textKirousis, Lefteris M. "Fast parallel constraint satisfaction." In Automata, Languages and Programming, 418–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-56939-1_91.
Full textJung, Victor, and Jean-Charles Régin. "Checking Constraint Satisfaction." In Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 332–47. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78230-6_21.
Full textHooker, J. N. "Convex Programming Methods for Global Optimization." In Global Optimization and Constraint Satisfaction, 46–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11425076_4.
Full textDvořák, Zdeněk, Daniel Král’, and Ondřej Pangrác. "Locally Consistent Constraint Satisfaction Problems." In Automata, Languages and Programming, 469–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-27836-8_41.
Full textRingwelski, Georg, and Youssef Hamadi. "Boosting Distributed Constraint Satisfaction." In Principles and Practice of Constraint Programming - CP 2005, 549–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11564751_41.
Full textCruz, Jorge, and Pedro Barahona. "Constraint Satisfaction Differential Problems." In Principles and Practice of Constraint Programming – CP 2003, 259–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45193-8_18.
Full textMitchell, David G. "Resolution and Constraint Satisfaction." In Principles and Practice of Constraint Programming – CP 2003, 555–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45193-8_38.
Full textConference papers on the topic "Constraint Satisfaction Programming"
Berrani, Sid-Ahmed, Haykel Boukadida, and Patrick Gros. "Constraint Satisfaction Programming for Video Summarization." In 2013 IEEE International Symposium on Multimedia (ISM). IEEE, 2013. http://dx.doi.org/10.1109/ism.2013.38.
Full textDev Gupta, Sharmi, Begum Genc, and Barry O'Sullivan. "Explanation in Constraint Satisfaction: A Survey." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/601.
Full textCanbaz, Baris, Bernard Yannou, and Pierre-Alain Yvars. "Constraint Programming Simulation of a Distributed Set-Based Design Framework With Control Indicators." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70857.
Full textLatour, Anna Louise D., Behrouz Babaki, and Siegfried Nijssen. "Stochastic Constraint Propagation for Mining Probabilistic Networks." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/159.
Full textScemama, G. "Signal plan design for complex intersections: a constraint satisfaction programming approach." In Eighth International Conference on Road Traffic Monitoring and Control. IEE, 1996. http://dx.doi.org/10.1049/cp:19960296.
Full textOrtiz-Bayliss, Jose Carlos, Ender Ozcan, Andrew J. Parkes, and Hugo Terashima-Marin. "A genetic programming hyper-heuristic: Turning features into heuristics for constraint satisfaction." In 2013 13th UK Workshop on Computational Intelligence (UKCI). IEEE, 2013. http://dx.doi.org/10.1109/ukci.2013.6651304.
Full textYannou, Bernard, Faysal Moreno, Henri J. Thevenot, and Timothy W. Simpson. "Faster Generation of Feasible Design Points." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85449.
Full textTalbot, Pierre. "Search Strategies as Synchronous Processes (Extended Abstract)." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/766.
Full textEriksson, Leif, and Victor Lagerkvist. "Improved Algorithms for Allen's Interval Algebra: a Dynamic Programming Approach." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/258.
Full textKoriche, Frédéric, Sylvain Lagrue, Éric Piette, and Sébastien Tabary. "Constraint-Based Symmetry Detection in General Game Playing." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/40.
Full text