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Volumn , Issue , 2010, Pages

Two novel Ant Colony Optimization approaches for Bayesian network structure learning

Author keywords

[No Author keywords available]

Indexed keywords

ANT-COLONY OPTIMIZATION; BAYESIAN NETWORK STRUCTURE; BENCH-MARK PROBLEMS; CHAIN STRUCTURE; COMPUTATION TIME; COMPUTATIONAL EFFORT; DATA VARIABLES; GA ALGORITHM; LARGE SIZES; LEARNING BAYESIAN NETWORKS; NOVEL ALGORITHM; NP-HARD PROBLEM; SOLUTION QUALITY; STRUCTURE-LEARNING;

EID: 79959397993     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2010.5586528     Document Type: Conference Paper
Times cited : (37)

References (37)
  • 1
    • 0002370418 scopus 로고
    • A tutorial on learning with Bayesian networks
    • MIT Press, Cambridge
    • D. Heckerman. A tutorial on learning with Bayesian networks in Learning in Graphical Models, 301-354, MIT Press, Cambridge, 1995.
    • (1995) Learning in Graphical Models , pp. 301-354
    • Heckerman, D.1
  • 2
    • 26944437287 scopus 로고    scopus 로고
    • Applications of Bayesian networks in meteorology
    • Springer-Verlag
    • R. Cano, Sordo & J. M Gutiérrez, Applications of Bayesian networks in meteorology. Advances in Bayesian networks Springer-Verlag. 309-327, 2004.
    • (2004) Advances in Bayesian Networks , pp. 309-327
    • Cano, R.1    Sordo2    Gutiérrez, J.M.3
  • 4
    • 0036268214 scopus 로고    scopus 로고
    • NasoNet, modeling the spread of nasopharyngeal cancer with networks of probabilistic events in discrete time
    • DOI 10.1016/S0933-3657(02)00027-1, PII S0933365702000271
    • S.F. Galán, F. Aguado. Modelling the Spread of Nasopharyngeal Cancer with Networks of Probabilistic Events in Discrete Time. Artificial Intelligence in Medicine. 25, 247-264. 2002. (Pubitemid 34586826)
    • (2002) Artificial Intelligence in Medicine , vol.25 , Issue.3 , pp. 247-264
    • Galan, S.F.1    Aguado, F.2    Diez, F.J.3    Mira, J.4
  • 5
    • 0001457227 scopus 로고
    • Robinson Counting labelled acyclic digraphs
    • F. Harary, editor, Academic Press, New York
    • W. Robert. Robinson Counting labelled acyclic digraphs. In F. Harary, editor, New Directions in the Theory of Graphs, Academic Press, New York. 239-273, 1973.
    • (1973) New Directions in the Theory of Graphs , pp. 239-273
    • Robert, W.1
  • 8
    • 0034174383 scopus 로고    scopus 로고
    • A new approach for learning belief networks using independence criteria
    • DOI 10.1016/S0888-613X(99)00042-0, PII S0888613X99000420
    • L.M. de Campos and J.F. Huete. A new approach for learning Bayesian networks using independence criteria. International Journal of Approximate Reasoning. 24, 11-37, 2000. (Pubitemid 34198912)
    • (2000) International Journal of Approximate Reasoning , vol.24 , Issue.1 , pp. 11-37
    • De Campos, L.M.1    Huete, J.F.2
  • 9
    • 34249832377 scopus 로고
    • A Bayesian Method for the Induction of Probabilistic Network from Data
    • F. Gregory Cooper, E. Herskovits, A Bayesian Method for the Induction of Probabilistic Network from Data, Machine Learning. 9,309-347,1992.
    • (1992) Machine Learning , vol.9 , pp. 309-347
    • Cooper, F.G.1    Herskovits, E.2
  • 11
    • 0000120766 scopus 로고
    • Estimating the dimensions of a model
    • G. Schwartz, Estimating the dimensions of a model. Ann. Stat., 6, 461-464.1979.
    • (1979) Ann. Stat. , vol.6 , pp. 461-464
    • Schwartz, G.1
  • 12
    • 9944259646 scopus 로고
    • Learning Bayesian networks: The combination of knowledge and statistical data
    • D. Heckerman, D. Geiger, and D. Chickering. Learning Bayesian networks: The combination of knowledge and statistical data. In KDD Workshop, 85-96, 1994
    • (1994) KDD Workshop , pp. 85-96
    • Heckerman, D.1    Geiger, D.2    Chickering, D.3
  • 13
    • 79959401716 scopus 로고    scopus 로고
    • Constructing structure learning algorithm
    • I. Tsamardino, E. Laura and F. Brown. Constructing structure learning algorithm, Machine Learning, 6, 31-78, 2006.
    • (2006) Machine Learning , vol.6 , pp. 31-78
    • Tsamardino, I.1    Laura, E.2    Brown, F.3
  • 15
    • 14044254184 scopus 로고    scopus 로고
    • Applying two-level simulated annealing on Bayesian structure learning to infer genetic networks
    • Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004
    • T. Wang, J. Touchman, and G. Xue Applying two- level simulated annealing on Bayesian structure learning to infer genetic networks. In Proceedings of the IEEE Computational Systems Bioinformatics Conference, 647-648, 2004. (Pubitemid 40276351)
    • (2004) Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 , pp. 647-648
    • Wang, T.1    Touchman, J.W.2    Xue, G.3
  • 16
    • 33645423346 scopus 로고    scopus 로고
    • Learning Bayesian Networks by Ant Colony Optimisation: Searching in two Different Spaces
    • L.M. de Campos, J.A. Gámez and J.M. Puerta Learning. Bayesian network by ant colony optimisation: Searching in two different spaces. Mathware and Soft Computing IX (2-3), 251-268, 2002. (Pubitemid 36439662)
    • (2002) MATHWARE AND SOFT COMPUTING , vol.9 , Issue.2-3 , pp. 251-268
    • Campos, L.M.1    Gamez, J.A.2    Puerta, J.M.3
  • 18
    • 55749086795 scopus 로고    scopus 로고
    • Learning of Bayesian networks by a local discovery ant colony algorithm
    • Pedro C. Pinto, A. Nägele, Mathäus Dejori, Thomas A. Runkler, João Miguel da Costa Sousa: Learning of Bayesian networks by a local discovery ant colony algorithm. CEC 2008, 2741-2748, 2008.
    • (2008) CEC 2008 , pp. 2741-2748
    • Pinto, P.C.1    Nägele, A.2    Dejori, M.3    Runkler, T.A.4    Da Costa Sousa, J.M.5
  • 20
    • 79959427276 scopus 로고    scopus 로고
    • Using ant colony optimization in learning Bayesian network equivalence classes
    • Xue Z. Wang and Rui Fa Li, editors
    • R. Daly, Q. Shen, and S. Aitken, Using ant colony optimization in learning Bayesian network equivalence classes. In Xue Z. Wang and Rui Fa Li, editors, Proceedings of the 2006 UK Workshop on Computational Intelligence, 111-118, 2006.
    • (2006) Proceedings of the 2006 UK Workshop on Computational Intelligence , pp. 111-118
    • Daly, R.1    Shen, Q.2    Aitken, S.3
  • 21
    • 68349117241 scopus 로고    scopus 로고
    • Learning Bayesian network equivalence classes with ant colony optimization
    • R. Daly and Q. Shen. Learning Bayesian network equivalence classes with ant colony optimization, Journal of Artificial Intelligence Research. 35, 391-447. 2009.
    • (2009) Journal of Artificial Intelligence Research , vol.35 , pp. 391-447
    • Daly, R.1    Shen, Q.2
  • 22
    • 0002012598 scopus 로고    scopus 로고
    • The ant colony optimization metaheuristic
    • D. Corne, M. Dorigo and F. Glover, Editors, McGraw-Hill
    • M. Dorigo and G. Di Caro, The ant colony optimization metaheuristic. In: D. Corne, M. Dorigo and F. Glover, Editors, New Ideas in Optimization, McGraw-Hill, 11-33.1999.
    • (1999) New Ideas in Optimization , pp. 11-33
    • Dorigo, M.1    Di Caro, G.2
  • 23
    • 84974719335 scopus 로고    scopus 로고
    • Ant systems for a dynamic TSP
    • M. Dorigo, G. D. Caro, and M. Samples, editors, Ant Algorithms
    • C.J. Eyckelhof and M. Snoek. Ant systems for a dynamic TSP. In M. Dorigo, G. D. Caro, and M. Samples, editors, Ant Algorithms, LNCS 2463, 88-99, 2002.
    • (2002) LNCS , vol.2463 , pp. 88-99
    • Eyckelhof, C.J.1    Snoek, M.2
  • 24
    • 0036085326 scopus 로고    scopus 로고
    • A new approach for solving large traveling salesman problem using evolution ant rules
    • IEEE Press
    • C.F.Tsai and C.W. Tsai. A new approach for solving large traveling salesman problem using evolution ant rules. In: Neural Networks, IJCNN 2002, IEEE Press, 2, 1540-1545, 2002.
    • (2002) Neural Networks, IJCNN 2002 , vol.2 , pp. 1540-1545
    • Tsai, C.F.1    Tsai, C.W.2
  • 25
    • 27644543634 scopus 로고    scopus 로고
    • Ant colony optimization theory: A survey
    • DOI 10.1016/j.tcs.2005.05.020, PII S0304397505003798
    • M. Dorigoa and C. Blum. Ant colony optimization theory: A survey. Theoretical Computer Science.344, 243-278. 2005. (Pubitemid 41554100)
    • (2005) Theoretical Computer Science , vol.344 , Issue.2-3 , pp. 243-278
    • Dorigo, M.1    Blum, C.2
  • 26
    • 28944454561 scopus 로고    scopus 로고
    • Ant colony optimization: Introduction and recent trends
    • C. Blum. Ant colony optimization: Introduction and recent trends. Phys. Life Reviews, 2, 353-373, 2005.
    • (2005) Phys. Life Reviews , vol.2 , pp. 353-373
    • Blum, C.1
  • 29
    • 69249161367 scopus 로고    scopus 로고
    • Online optimization of a colour sorting assembly buffer using ant colony optimization
    • S. A. Hartmann and T. A. Runkler. Online optimization of a colour sorting assembly buffer using ant colony optimization. In Proc. Operations Res., 415-420, 2007.
    • (2007) Proc. Operations Res. , pp. 415-420
    • Hartmann, S.A.1    Runkler, T.A.2
  • 30
    • 12244288095 scopus 로고    scopus 로고
    • Stochastic Local Algorithms for Learning Belief Networks: Searching in the Space of the Orderings
    • L.M. de Campos and J.M. Puerta. Stochastic local search algorithms for learning belief networks: Searching in the space of orderings. Lecture Notes in Artificial Intelligence, 2143:228-239, 2001. (Pubitemid 33334675)
    • (2001) LECTURE NOTES IN COMPUTER SCIENCE , Issue.2143 , pp. 228-239
    • De Campos, L.M.1    Puerta, J.M.2
  • 31
    • 33746035971 scopus 로고    scopus 로고
    • The max-min hill climbing BN structure learning algorithm
    • Oct.
    • I. Tsamardinos, L.F. Brown, and C. F. Aliferis, The max-min hill climbing BN structure learning algorithm. Mach. Learning, 65(1), 31-78, Oct. 2006.
    • (2006) Mach. Learning , vol.65 , Issue.1 , pp. 31-78
    • Tsamardinos, I.1    Brown, L.F.2    Aliferis, C.F.3
  • 32
    • 34548087879 scopus 로고    scopus 로고
    • A chain-model genetic algorithm for Bayesian network structure learning
    • Proceedings of the 9th annual conference on Genetic and evolutionary computation (GECCO)
    • R. Kabli, F. Herrmann, J. McCall. A chain-model genetic algorithm for Bayesian network structure learning, Proceedings of the 9th annual conference on Genetic and evolutionary computation (GECCO). In IEEE World Congress on Computational Intelligence, 1264-1271, 2007.
    • (2007) IEEE World Congress on Computational Intelligence , pp. 1264-1271
    • Kabli, R.1    Herrmann, F.2    McCall, J.3
  • 34
    • 0001006209 scopus 로고
    • Local computations with probabilities on graphical structures and their application to expert systems
    • S. L. Lauritzen and D. J. Spiegelhalter. Local computations with probabilities on graphical structures and their application to expert systems. Journal of the Royal Statistical Society. 50(2), 157-224, 1988.
    • (1988) Journal of the Royal Statistical Society , vol.50 , Issue.2 , pp. 157-224
    • Lauritzen, S.L.1    Spiegelhalter, D.J.2


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