Abstract
Page-based Linear Genetic Programming (GP) is proposed
in which individuals are described in terms of a number
of pages. Pages are expressed in terms of a fixed
number of instructions, constant for all individuals in
the population. Pairwise crossover results in the
swapping of single pages, thus individuals are of a
fixed number of instructions. Head-to-head comparison
with Tree structured GP and block-based Linear GP
indicates that the page-based approach evolves succinct
solutions without penalizing generalization ability.
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