메뉴 건너뛰기




Volumn 35, Issue 3, 2014, Pages 48-60

Algorithm selection for combinatorial search problems: A survey

Author keywords

[No Author keywords available]

Indexed keywords

COMBINATORIAL MATHEMATICS; SURVEYS;

EID: 84902498817     PISSN: 07384602     EISSN: None     Source Type: Journal    
DOI: 10.1609/aimag.v35i3.2460     Document Type: Review
Times cited : (163)

References (58)
  • 1
    • 85152577740 scopus 로고
    • Generalizing from case studies: A case study
    • 1-10. San Francisco, CA: Morgan Kaufmann Publishers Inc
    • Aha, D. W. 1992. Generalizing from Case Studies: A Case Study. In Proceedings of the 9th International Workshop on Machine Learning, 1-10. San Francisco, CA: Morgan Kaufmann Publishers Inc.
    • (1992) Proceedings of the 9th International Workshop on Machine Learning
    • Aha, D.W.1
  • 3
    • 84893463221 scopus 로고    scopus 로고
    • Online heuristic selection in constraint programming
    • Paper presented at Lake Arrowhead, CA, July 8-10
    • Arbelaez, A.; Hamadi, Y.; and Sebag, M. 2009. Online Heuristic Selection in Constraint Programming. Paper presented at the Symposium on Combinatorial Search, Lake Arrowhead, CA, July 8-10.
    • (2009) The Symposium on Combinatorial Search
    • Arbelaez, A.1    Hamadi, Y.2    Sebag, M.3
  • 6
    • 85118837783 scopus 로고
    • Addressing the selective superiority problem: Automatic algorithm/model class selection
    • San Francisco: Morgan Kaufmann Publishers, Inc
    • Brodley, C. E. 1993. Addressing the Selective Superiority Problem: Automatic Algorithm/Model Class Selection. In Proceedings of the International Conference on Machine Learning, 17-24. San Francisco: Morgan Kaufmann Publishers, Inc.
    • (1993) Proceedings of the International Conference on Machine Learning , pp. 17-24
    • Brodley, C.E.1
  • 13
    • 84907661572 scopus 로고    scopus 로고
    • Statistical selection among problem-solving methods
    • Carnegie Mellon University, Pittsburgh, PA
    • Fink, E. 1997. Statistical Selection Among Problem-Solving Methods. Technical Report CMU-CS-97-101, Carnegie Mellon University, Pittsburgh, PA.
    • (1997) Technical Report CMU-CS-97-101
    • Fink, E.1
  • 14
    • 42449117713 scopus 로고    scopus 로고
    • Automated discovery of local search heuristics for satisfiability testing
    • Fukunaga, A. S. 2008. Automated Discovery of Local Search Heuristics for Satisfiability Testing. Evolutionary Computation 16: 31-61.
    • (2008) Evolutionary Computatio , vol.16 , pp. 31-61
    • Fukunaga, A.S.1
  • 15
    • 0036923148 scopus 로고    scopus 로고
    • Automated discovery of composite sat variable-selection heuristics
    • Menlo Park, CA: AAAI Press
    • Fukunaga, A. S. 2002. Automated Discovery of Composite SAT Variable-Selection Heuristics. In Proceedings of the 18th National Conference on Artificial Intelligence, 641-648. Menlo Park, CA: AAAI Press. dx.doi.org/10.1162/evco.2008.16. 1.31
    • (2002) Proceedings of the 18th National Conference on Artificial Intelligence , pp. 641-648
    • Fukunaga, A.S.1
  • 22
    • 9244255265 scopus 로고    scopus 로고
    • Groups of diverse problem solvers can outperform groups of high-ability problem solvers
    • Hong, L., and Page, S. E. 2004. Groups of Diverse Problem Solvers can Outperform Groups of High-Ability Problem Solvers. In Proceedings of the National Academy of Sciences of the United States of America 101(46): 16385-16389. dx.doi.org/10.1073/pnas.0403723101
    • (2004) Proceedings of the National Academy of Sciences of the United States of America , vol.101 , Issue.46 , pp. 16385-16389
    • Hong, L.1    Page, S.E.2
  • 24
    • 0031035643 scopus 로고    scopus 로고
    • An economics approach to hard computational problems
    • Huberman, B. A.; Lukose, R. M.; and Hogg, T. 1997. An Economics Approach to Hard Computational Problems. Science 275(5296): 51-54. dx.doi.org/10.1126/science.275.5296.51
    • (1997) Science , vol.275 , Issue.5296 , pp. 51-54
    • Huberman, B.A.1    Lukose, R.M.2    Hogg, T.3
  • 28
    • 84878788330 scopus 로고    scopus 로고
    • Hybrid regression-classification models for algorithm selection
    • Amsterdam, The Netherlands: IOS Press
    • Kotthoff, L. 2012. Hybrid Regression-Classification Models for Algorithm Selection. In Proceedings of the 20th European Conference on Artificial Intelligence, 480-485. Amsterdam, The Netherlands: IOS Press.
    • (2012) Proceedings of the 20th European Conference on Artificial Intelligence , pp. 480-485
    • Kotthoff, L.1
  • 29
    • 84865481979 scopus 로고    scopus 로고
    • An evaluation of machine learning in algorithm selection for search problems
    • Kotthoff, L.; Gent, I. P.; and Miguel, I. 2012. An Evaluation of Machine Learning in Algorithm Selection for Search Problems. AI Communications 25(3): 257-270.
    • (2012) AI Communications , vol.25 , Issue.3 , pp. 257-270
    • Kotthoff, L.1    Gent, I.P.2    Miguel, I.3
  • 31
    • 0020767025 scopus 로고
    • Learning search strategies through discrimination
    • Langley, P. 1983. Learning Search Strategies Through Discrimination. International Journal of Man-Machine Studies 18(6): 513-541. dx.doi.org/10.1016/S0020-7373(83)80030-
    • (1983) International Journal of Man-Machine Studies , vol.18 , Issue.6 , pp. 513-541
    • Langley, P.1
  • 35
    • 0030232147 scopus 로고    scopus 로고
    • Automatically configuring constraint satisfaction programs: A case study
    • Minton, S. 1996. Automatically Configuring Constraint Satisfaction Programs: A Case Study. Constraints 1(1-2): 7-43. dx.doi.org/10.1007/BF00143877
    • (1996) Constraints , vol.1 , Issue.1-2 , pp. 7-43
    • Minton, S.1
  • 39
    • 58549118916 scopus 로고    scopus 로고
    • A self-adaptive multi-engine solver for quantified boolean formulas
    • Pulina, L., and Tacchella, A. 2009. A Self-Adaptive Multi-Engine Solver for Quantified Boolean Formulas. Constraints 14(1): 80-116.
    • (2009) Constraints , vol.14 , Issue.1 , pp. 80-116
    • Pulina, L.1    Tacchella, A.2
  • 41
    • 0003056605 scopus 로고
    • The algorithm selection problem
    • Rice, J. R. 1976. The Algorithm Selection Problem. Advances in Computers 15: 65-118. dx.doi.org/10.1016/S0065-2458(08)60520-3
    • (1976) Advances in Computer , vol.15 , pp. 65-118
    • Rice, J.R.1
  • 46
    • 49749086726 scopus 로고    scopus 로고
    • Cross-disciplinary perspectives on meta-learning for algorithm selection
    • Article 6
    • Smith-Miles, K. A. 2008. Cross-Disciplinary Perspectives on Meta-Learning for Algorithm Selection. ACM Computing Surveys 41(1), Article 6. dx.doi.org/10.1145/1456650.1456656
    • (2008) ACM Computing Surveys , vol.41 , Issue.1
    • Smith-Miles, K.A.1
  • 47
    • 70349119049 scopus 로고    scopus 로고
    • Heuristics for dynamically adapting propagation in constraint satisfaction problems
    • Stergiou, K. 2009. Heuristics for Dynamically Adapting Propagation In Constraint Satisfaction Problems. AI Communications 22(3): 125-141.
    • (2009) AI Communications , vol.22 , Issue.3 , pp. 125-141
    • Stergiou, K.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.