Exact Bayesian network learning in estimation of distribution algorithms

2007 IEEE Congress on Evolutionary Computation, CEC 2007

Volumn , Issue , 2007, Pages 1051-1058

  Echegoyen, Carlos ^a   Lozano, Jose A ^a   Santana, Roberto ^a   Larrañaga, Pedro ^a  

^a UNIVERSITY OF THE BASQUE COUNTRY UPV EHU   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ESTIMATION OF BAYESIAN NETWORK ALGORITHM (EBNA); ESTIMATION OF DISTRIBUTION ALGORITHMS (EDA);

BAYESIAN NETWORKS; LEARNING SYSTEMS; MATHEMATICAL MODELS;

EVOLUTIONARY ALGORITHMS;

EID: 51849108416     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2007.4424586     Document Type: Conference Paper

References (38)

1. P. Larrañaga and J. A. Lozano, Eds., Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation. Boston/Dordrecht/London: Kluwer Academic Publishers, 2002.
2. H. Mühlenbein and G. Paaß, "From recombination of genes to the estimation of distributions I. Binary parameters," in Parallel Problem Solving from Nature - PPSN IV, H.-M. Voigt, W. Ebeling, I. Rechenberg, and H.-P. Schwefel, Eds. Berlin: Springer Verlag, 1996, pp. 178-187, LNCS 1141.
3. D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison-Wesley, 1989.
4. D. Heckerman, D. Geiger, and D. M. Chickering, "Learning Bayesian networks: The combination of knowledge and statistical data," Machine Learning, vol. 20, pp. 197-243, 1995.
5. R. Etxeberria and P. Larrañaga, "Global optimization using Bayesian networks," in Proceedings of the Second Symposium on Artificial Intelligence (CIMAF-99), A. Ochoa, M. R. Soto, and R. Santana, Eds., Habana, Cuba, 1999, pp. 151-173.
6. H. Mühlenbein and T. Mahnig, "Evolutionary synthesis of Bayesian networks for optimization," in Advances in Evolutionary Synthesis of Intelligent Agents, M. Patel, V. Honavar, and K. Balakrishnan, Eds. Cambridge, Mass.: MIT Press, 2001, pp. 429-455.
7. M. Pelikan, D. E. Goldberg, and E. Cantú-Paz, "BOA: The Bayesian optimization algorithm," in Proceedings of the Genetic and Evolutionary Computation Conference GECCO-1999, W. Banzhaf, J. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela, and R. E. Smith, Eds., vol. I. Orlando, FL: Morgan Kaufmann Publishers, San Francisco, CA, 1999, pp. 525-532.
8. M. R. Soto, A. Ochoa, S. Acid, and L. M. Campos, "Bayesian evolutionary algorithms based on simplified models," in Proceedings of the Second Symposium on Artificial Intelligence (CIMAF-99), A. Ochoa, M. R. Soto, and R. Santana, Eds., Habana, Cuba, March 1999, pp. 360-367.
9. R. Höns, "Estimation of Distribution Algorithms and Minimum Relative Entropy," Ph.D. dissertation, University of Bonn, Bonn, Germany, 2006.
10. H. Mühlenbein and R. Höns, "The estimation of distributions and the minimum relative entropy principle," Evolutionary Computation, vol. 13, no. 1, pp. 1-27, 2005.
11. R. Santana, A. Ochoa, and M. R. Soto, "The mixture of trees factorized distribution algorithm," in Proceedings of the Genetic and Evolutionary Computation Conference GECCO-2001. San Francisco, CA: Morgan Kaufmann Publishers, 2001, pp. 543-550.
12. R. Santana, "An analysis of the performance of the mixture of trees factorized distribution algorithm when priors and adaptive learning are used," Institute of Cybernetics, Mathematics and Physics, Havana, Cuba, Tech. Rep. ICIMAF 2002-180, March 2002.
13. E. Bengoetxea, "Inexact graph matching using estimation of distribution algorithms," Ph.D. dissertation, Ecole Nationale Supérieure des Télécommunications, 2003.
14. M. Hauschild, M. Pelikan, C. Lima, and K. Sastry, "Analyzing probabilistic models in hierarchical boa on traps and spin glasses," Missouri Estimation of Distribution Algorithms Laboratory, MEDAL Report No. 2007001, 2007.
15. C. F. Lima, M. Pelikan, D. E. Goldberg, F. G. Lobo, K. Sastry, and M. Hauschild, "Influence of selection and replacement strategies on linkage learning in boa," University of Illinois at Urbana-Champaign, Illinois Genetic Algorithms Laboratory, Urbana, IL, IlliGAL Report No. 2007013, 2007.
16. D. Eaton and K. Murphy, "Exact Bayesian structure learning from uncertain interventions," in Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007.
17. M. Koivisto and K. Sood, "Exact Bayesian structure discovery in Bayesian networks," Journal of Machine Learning Research, vol. 5, pp. 549-573, 2004.
18. T. Silander and P. Myllymaki, "A simple approach for finding the globally optimal Bayesian network structure," in Proceedings of the 22th Annual Conference on Uncertainty in Artificial Intelligence (UAI-2006). Morgan Kaufmann Publishers, 2006.
19. A. Singh and A. Moore, "Finding optimal Bayesian networks by dynamic programming," Carnegie Mellon University, Tech. Rep., June 2005.
20. G. Schwarz, "Estimating the dimension of a model." Annals of Statistics, vol. 7, no. 2, pp. 461-464, 1978.
21. D. M. Chickering, D. Geiger, and D. Heckerman, "Learning Bayesian networks is NP-hard," Microsoft Research, Redmond, WA, Tech. Rep. MSR-TR-94-17, 1994. [Online]. Available: ftp://research.microsoft.com/pub/Tech- Reports/Summer94/TR-94-17.PS
22. E. Castillo, J. M. Gutierrez, and A. S. Hadi, Expert Systems and Probabilistic Network Models. Springer-Verlag, 1997.
23. W. Buntine, "Theory refinement in Bayesian networks," 1991, pp. 52-60.
24. J. A. Lozano, R. Sagarna, and P. Larrañaga, "Parallel estimation of Bayesian networks algorithms," in Evolutionary Computation and Probabilistic Graphical Models. Proceedings of the Third Symposium on Adaptive Systems (ISAS-2001), Habana, Cuba, March 2001, pp. 137-144.
25. R. Blanco and J. A. Lozano, Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation. Boston/Dordrecht/London: Kluwer Academic Publishers, 2002, ch. An empirical comparison of discrete Estimation of Distribution Algorithms, pp. 163-176.
26. R. Sagarna and P. Larrañaga, Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation. Boston Dordrecht London: Kluwer Academic Publishers, 2002, ch. Solving the 0-1 knapsack problem with EDAs, pp. 191-206.
27. I. Inza, P. Larrañaga, and B. Sierra, Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation. Boston/Dordrecht/London: Kluwer Academic Publishers, 2002, ch. Feature subset selection by Estimation of Distribution Algorithms, pp. 265-290.
28. J. A. Lozano, P. Larrañaga, I. Inza, and E. Bengoetxea, Eds., Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms. Springer-Verlag, 2006.
29. S. Baluja and S. Davies, "Using optimal dependency-trees for combinatorial optimization: Learning the structure of the search space," in Proceedings of the 14th International Conference on Machine Learning. Morgan Kaufmann, 1997, pp. 30-38.
30. H. Mühlenbein, T. Mahnig, and A. Ochoa, "Schemata, distributions and graphical models in evolutionary optimization," Journal of Heuristics, vol. 5, no. 2, pp. 213-247, 1999.
31. M. Pelikan, K. Sastry, and D. E. Goldberg, "Scalability of the bayesian optimization algorithm," International Journal of Approximate Reasoning, vol. 31, no. 3, pp. 221-258, 2002.
32. R. Santana, P. Larrañaga, and J. A. Lozano, "Interactions and dependencies in estimation of distribution algorithms," in Proceedings of the 2005 Congress on Evolutionary Computation CEC-2005. Edinburgh, U.K.: IEEE Press, 2005, pp. 1418-1425.
33. L. Kallel, B. Naudts, and R. Reeves, "Properties of fitness functions and search landscapes," in Theoretical Aspects of Evolutionary Computing, L. Kallel, B. Naudts, and A. Rogers, Eds. Springer Verlag, 2000, pp. 177-208.
34. R. Santana, "Estimation of distribution algorithms with Kikuchi approximations," Evolutionary Computation, vol. 13, no. 1, pp. 67-97, 2005.
35. R. Santana, P. Larrañaga, and J. A. Lozano, "The role of a priori information in the minimization of contact potentials by means of estimation of distribution algorithms," in Proceedings of the Fifth European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, ser. Lecture Notes in Computer Science, E. Marchiori, J. H. Moore, and J. C. Rajapakse, Eds., vol. 4447, 2007, pp. 247-257.
36. A. Ochoa and M. R. Soto, "Linking entropy to estimation of distribution algorithms," in Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms, J. A. Lozano, P. Larrañaga, I. Inza, and E. Bengoetxea, Eds. Springer-Verlag, 2006, pp. 1-38.
37. P. A. Bosman and D. Thierens, "Linkage information processing in distribution estimation algorithms," in Proceedings of the Genetic and Evolutionary Computation Conference GECCO-1999, W. Banzhaf, J. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela, and R. E. Smith, Eds., vol. I. Orlando, FL: Morgan Kaufmann Publishers, San Francisco, CA, 1999, pp. 60-67.
38. R. Santana, E. P. de León, and A. Ochoa, "The edge incident model," in Proceedings of the Second Symposium on Artificial Intelligence (CIMAF-99), A. Ochoa, M. R. Soto, and R. Santana, Eds., Habana, Cuba, March 1999, pp. 352-359.