In symbolic regression (Koza, 1992), a label y is provided
for every ~x and an explicit symbolic relationship of
the form y = f(~x) is sought. Unlike traditional statistical
regressions that fit parameters to an equation of a given
form, symbolic regression searches both the parameters
and the form of equations simultaneously (Schmidt &
Lipson, 2009). Scientists have attempted to identify and
document analytical laws that underlie physical phenomena
in nature. Despite the prevalence of computing power