Abstract
In the last two years the schema theory for Genetic
Programming (GP) has been applied to the problem of
understanding the length biases of a variety of
crossover and mutation operators on variable length
linear structures. In these initial papers, operators
were studied in isolation. In practice, however, they
are typically used in various combinations, and in this
paper we present the first schema theory analysis of
the complex interactions of multiple operators. In
particular, we apply the schema theory to the use of
standard subtree crossover, full mutation, and grow
mutation (in varying proportions) to variable length
linear structures in the one-then-zeros problem. We
then show how the results can be used to guide choices
about the relative proportion of these operators in
order to achieve certain structural goals during a
run.
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