  Modern evolutionary computation utilizes heuristic optimizations based upon
concepts borrowed from the Darwinian theory of natural selection. We believe
that a vital direction in this field must be algorithms that model the activity
of genomic parasites, such as transposons, in biological evolution. This
publication is our first step in the direction of developing a minimal
assortment of algorithms that simulate the role of genomic parasites.
Specifically, we started in the domain of genetic algorithms (GA) and selected
the Artificial Ant Problem as a test case. We define these artificial
transposons as a fragment of an ant's code that possesses properties that cause
it to stand apart from the rest. We concluded that artificial transposons,
analogous to real transposons, are truly capable of acting as intelligent
mutators that adapt in response to an evolutionary problem in the course of
co-evolution with their hosts.
