abstract = "In nature, systems with enormous numbers of components
(i.e. cells) are evolved from a relatively small
genotype. It has not yet been demonstrated that
artificial evolution is sufficient to make such a
system evolvable. Consequently researchers have been
investigating forms of computational development that
may allow more evolvable systems. The approaches taken
have largely used re-writing, multi-cellularity, or
genetic regulation. In many cases it has been difficult
to produce general purpose computation from such
systems. In this paper we introduce computational
development using a form of Cartesian Genetic
Programming that includes self-modification operations.
One advantage of this approach is that ab initio the
system can be used to solve computational problems. We
present results on a number of problems and demonstrate
the characteristics and advantages that
self-modification brings.",
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).