Large hinge width on sparse random hypergraphs

IJCAI International Joint Conference on Artificial Intelligence

Volumn , Issue , 2011, Pages 611-616

  Liu, Tian ^a   Lin, Xiaxiang ^a   Wang, Chaoyi ^a   Su, Kaile ^a   Xu, Ke ^b  

^a PEKING UNIVERSITY   (China)

^b BEIHANG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

HIGH PROBABILITY; HYPER GRAPH; HYPEREDGES; PROBABILITY P; RANDOM CONSTRAINT SATISFACTION PROBLEMS; RANDOM GRAPHS; RANDOM INSTANCE; SATISFIABILITY THRESHOLD;

ARTIFICIAL INTELLIGENCE; FORMAL LOGIC;

GRAPH THEORY;

EID: 84881069549     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5591/978-1-57735-516-8/IJCAI11-109     Document Type: Conference Paper

References (24)

1. C. Ansótegui, R. Béjar, C. Fernàndez, and C. Mateu. On balanced csps with high treewidth. In Proc. AAAI, pages 161-166, 2007.
2. C. Ansótegui, M. L. Bonet, J. Levy, and F. Manyà. Measuring the hardness of sat instances. In Proc. AAAI, pages 222-228, 2008.
3. P. Cheeseman, R. Kanefsky, and W. Taylor. Where the really hard problems are. In Proc. IJCAI, pages 163-169, 1991.
4. D. Cohen, P. Jeavons, and M. Gyssens. A unified theory of structural tractability for constraint satisfaction problems. J. Computer and System Sci., 74(5):721-743, 2008. (Pubitemid 351685701)
5. S. A. Cook and D. G. Mitchell. Finding hard instances of the satisfiability problem: a survey. In DIMACS Series, Vol. 35, pages 1-17, 1997.
6. Rina Dechter. Constraint Processing. Morgan Kaufmann, 2003.
7. R. Dechter. Tractable structures for constraint satisfaction problems. In Handbook of constraint programming, pages 209-244, 2006.
8. Y. Gao and J. Culberson. Consitency and random constraint satisfaction problems. J. Artif. Intell. Res. (JAIR), 28:517-557, 2007. (Pubitemid 46790309)
9. Y. Gao. Phase transition of tractability in constraint satisfaction and bayesian network inference. In Proc. UAI, pages 265-271, 2003.
10. C. Gomes and T. Walsh. Randomness and structures. In Handbook of constraint programming, pages 639-664, 2006.
11. G. Gottlob, N. Leone, and F. Scarcello. A comparison of structural csp decomposition methods. Artif. Intell., 124(2):243-282, 2000. (Pubitemid 32029459)
12. G. Gottlob, N. Leone, and F. Scarcello. The complexity of acyclic conjunctive queries. J. American Comput. Mach., 43(3):431-498, 2001.
13. G. Greco and F. Scarcello. On the power of structural decompositions of graph-based representations of constraint problems. Artif. Intell., 174(5-6):382-409, 2010.
14. M. Gyssens and J. Paredaens. A decomposition methodology for acyclic database. In Advances in Database Theory, Vol. 2, pages 85-122. Plenum Press, 1984.
15. M. Gyssens, P. Jeavons, and D. Cohen. Decomposing constraint satisfaction problems using database techniques. Artif. Intell., 66(1):57-89, 1994.
16. S. Janson, T. Luczak, and A. Rucinski. Random Graphs. John Wiley & Sons, Inc., 2000.
17. T. Kloks. Treewidth: computations and approximations, LNCS 842. Springer, 1994.
18. Christophe Lecoutre. Constraint Networks: Techniques and Algorithms. ISTE/Wiley, 2009.
19. D. G. Mitchell, B. Selman, and H. J. Levesque. Hard and easy distributions of sat problems. In Proc. AAAI, pages 459-465, 1992.
20. M. Mitzenmacher and E. Upfal. Probability and Computing. Cambridge University Press, 2005.
21. B. Selman, D. G. Mitchell, and H. J. Levesque. Generating hard satisfiability problems. Artif. Intell., 81:17-29, 1996. (Pubitemid 126349547)
22. K. Xu and W. Li. Exact phase transitions in random constraint satisfaction problems. J. Artif. Intell. Res. (JAIR), 12:93-103, 2000.
23. K. Xu and W. Li. Many hard examples in exact phase transitions. Theoret. Comput. Sci, 355(3):291-302, 2006.
24. K. Xu, F. Boussemart, F. Hemery, and C. Lecoutre. Random constraint satisfaction: Easy generation of hard (satisfiable) instances. Artif. Intell., 171:514-534, 2007. (Pubitemid 46828981)