Crossover is a method of recombining two
strings of genetic material. |
Simplest is the single-point crossover: snip
both strings at the same location and interchange the pieces. |
Another method, multiple-point crossover, involves recombining the strings at
several locations. We shall consider only single-point crossovers. |
First here is an illustration of single-point corssover
using two sentences. |
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Click the picture to animate. |
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Here is an example using the CA classifier system: |
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Here are patterns generated by the parents, both from the same
random initial distribution. Click on the small picture for a larger version in a new window. |
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Here are patterns generated by the children, both from the same
random initial distribution. Click on the small picture for a larger version in a new window. |
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Crossover allows large excursions in genotype space. It is aided by
Holland's Schema theorem: combinations of genes that increase fitness tend to be
preserved and amplified by crossover in large populations. |
Return to Genetic Algorithms and Artificial Evolution.
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