Abstract
Abstract Recombination is a commonly used genetic
operator in artificial and computational evolutionary
systems. It has been empirically shown to be essential
for evolutionary processes. However, little has been
done to analyze the effects of recombination on
quantitative genotypic and phenotypic properties. The
majority of studies only consider mutation, mainly due
to the more serious consequences of recombination in
reorganizing entire genomes. Here we adopt methods from
evolutionary biology to analyze a simple, yet
representative, genetic programming method, linear
genetic programming. We demonstrate that recombination
has less disruptive effects on phenotype than mutation,
that it accelerates novel phenotypic exploration, and
that it particularly promotes robust phenotypes and
evolves genotypic robustness and synergistic epistasis.
Our results corroborate an explanation for the
prevalence of recombination in complex living
organisms, and helps elucidate a better understanding
of the evolutionary mechanisms involved in the design
of complex artificial evolutionary systems and
intelligent algorithms.
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