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  5. From Genetic Variation to Probabilistic Modeling

    Genetic algorithms ⦓GAs) [53, 83] are stochastic optimization methods inspired by natural evolution and genetics. Over the last few decades, GAs have...
    Martin Pelikan in Hierarchical Bayesian Optimization Algorithm
    Chapter

  6. Hierarchical Bayesian Optimization Algorithm

    The previous chapter has discussed how hierarchy can be used to reduce problem complexity in black-box optimization. Additionally, the chapter has...
    Martin Pelikan in Hierarchical Bayesian Optimization Algorithm
    Chapter

  12. The Challenge of Hierarchical Difficulty

    Thus far, we have examined the Bayesian optimization algorithm (BOA), empirical results of its application to several problems of bounded difficulty,...
    Martin Pelikan in Hierarchical Bayesian Optimization Algorithm
    Chapter

  20. Hierarchical BOA in the Real World

    The last chapter designed hBOA, which was shown to provide scalable solution for hierarchical traps. Since hierarchical traps were designed to test...
    Martin Pelikan in Hierarchical Bayesian Optimization Algorithm
    Chapter
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