abstract = "Genetic Programming was first introduced by Koza using
tree representation together with a crossover technique
in which random sub-branches of the parents' trees are
swapped to create the offspring. Later Miller and
Thomson introduced Cartesian Genetic Programming, which
uses directed graphs as a representation to replace the
tree structures originally introduced by Koza.
Cartesian Genetic Programming has been shown to perform
better than the traditional Genetic Programming; but it
does not use crossover to create offspring, it is
implemented using mutation only. In this paper a new
crossover method in Genetic Programming is introduced.
The new technique is based on an adaptation of the
Cartesian Genetic Programming representation and is
tested on two simple regression problems. It is shown
that by implementing the new crossover technique,
convergence is faster than that of using mutation only
in the Cartesian Genetic Programming method.",
notes = "GECCO-2007 A joint meeting of the sixteenth
international conference on genetic algorithms
(ICGA-2007) and the twelfth annual genetic programming
conference (GP-2007).