The relationship between the genotype and phenotype of organisms plays a key
role in the evolutionary process.  While Evolutionary Computation (EC) models
have traditionally taken biological inspiration in the design of many key
model components (e.g., genetic mutation and crossover, populations under
natural selection, etc.), there is a need for more biological input in
specifying how a genotype forms a phenotype.

There are two powerful theoretical abstractions used in biology for explaining
the evolutionary basis of phenotypic development.  The first is that there is
a sequence of hereditary information (the genotype) passed from one generation
to the next.  The second is that genes extracted from this sequence interact
to form networks of regulation that, when coupled with environmental factors,
control the development of an organism (the phenotype).  An abstract model of
gene regulation exists in the form of the Artificial Genome.  This model
provides a principled approach to extracting regulatory networks of genes from
sequence-level information.  L-systems provide a mature framework for modelling
developmental phenotypes interacting within environments.

This paper takes a step towards integrating these two models, providing a
biologically-inspired modelling framework that bridges the chasm between
processes occurring in evolutionary timescales, and those occurring within
individual lifetimes.