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Martin Pelikan, Kumara Sastry, Martin V. Butz, and David E. Goldberg  (Make Corrections)  
MEDAL Report No. 2006001 March 2006 The hierarchical Bayesian optimization...



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Abstract: This paper describes a class of random additively decomposable problems with and without interactions between the subproblems and tests hBOA on a large number of random instances of the proposed class of problems. The performance of hBOA is compared to that of the simple genetic algorithm with standard crossover and mutation operators, the univariate marginal distribution algorithm, and the hill climbing with bitflip mutation. The results confirm that hBOA achieves quadratic or subquadratic... (Update)

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BibTeX entry:   (Update)

@misc{ no-martin,
  author = "Medal Report No",
  title = "Martin Pelikan, Kumara Sastry, Martin V. Butz, and David E. Goldberg",
  url = "citeseer.ist.psu.edu/761643.html" }
Citations (may not include all citations):
2138   Genetic algorithms in search (context) - Goldberg - 1989
1931   Adaptation in natural and artificial systems (context) - Holland - 1975
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57   How genetic algorithms really work (context) - Muhlenbein - 1992
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32   A Bayesian approach to learning Bayesian networks with local.. - Chickering, Heckerman et al. - 1997
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15   Morphing: Combining structure and randomness - Gent, Hoos et al. - 1999
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9   Katholieke Universiteit Leuven (context) - Thierens, design et al. - 1995
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