abstract = "This paper describes a new program evolution method
named PORTS (Program Optimization by Random Tree
Sampling) which is motivated by the idea of
preservation and control of tree fragments. We
hypothesize that to reconstruct building blocks
efficiently, tree fragments of any size should be
preserved into the next generation, according to their
differential fitnesses. PORTS creates a new individual
by sampling from the promising trees by traversing and
transition between trees instead of subtree crossover
and mutation. Because the size of a fragment preserved
during a generation update follows a geometric
distribution, merits of the method are that it is
relatively easy to predict the behavior of tree
fragments over time and to control sampling size, by
changing a single parameter. Our experimental results
on three benchmark problems show that the performance
of PORTS is competitive with SGP (Simple Genetic
Programming). And we observed that there is a
significant difference of fragment distribution between
PORTS and simple GP.",
notes = "GECCO-2009 A joint meeting of the eighteenth
international conference on genetic algorithms
(ICGA-2009) and the fourteenth annual genetic
programming conference (GP-2009).