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Building blocks, cohort genetic algorithms, and hyperplane-defined functions.

J H Holland
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Abstract

Building blocks are a ubiquitous feature at all levels of human understanding, froin perception through science and innovation. Genetic algorithms are designed to exploit this prevalence. A new, more robust class of genetic algorithms, cohort genetic algorithms (cGA's), provides substantial advantages in exploring search spaces for building blocks while exploiting building blocks already found. To test these capabilities, a new, general class of test functions, the hyperplane-defined functions (hdf's), has been designed. Hdf's offer the means of tracing the origin of each advance in performance; at the same time hdf's are resistant to reverse engineering, so that algorithms cannot be designed to take advantage of the characteristics of particular examples.

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BibTeXRIS

J H Holland. 2000. Building blocks, cohort genetic algorithms, and hyperplane-defined functions.. https://doi.org/10.1162/106365600568220

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