1 research outputs found
The Benefit of Sex in Noisy Evolutionary Search
The benefit of sexual recombination is one of the most fundamental questions
both in population genetics and evolutionary computation. It is widely believed
that recombination helps solving difficult optimization problems. We present
the first result, which rigorously proves that it is beneficial to use sexual
recombination in an uncertain environment with a noisy fitness function. For
this, we model sexual recombination with a simple estimation of distribution
algorithm called the Compact Genetic Algorithm (cGA), which we compare with the
classical EA. For a simple noisy fitness function with additive
Gaussian posterior noise , we prove that the
mutation-only EA typically cannot handle noise in polynomial time for
large enough while the cGA runs in polynomial time as long as the
population size is not too small. This shows that in this uncertain environment
sexual recombination is provably beneficial. We observe the same behavior in a
small empirical study