Gene Expression Programming (GEP) is a learning algorithm and what it
learns specifically is about relationships between variables in sets of
data and then builds models to explain these relationships. How learning
algorithms build models or discover solutions to problems varies, with
some simulating networks of neurons and others simulating evolution
through natural selection. Gene Expression Programming belongs to the
latter group....
Karva notation was developed specifically for Gene Expression
Programming (GEP) and consists of a universal way of compactly
representing any mathematical or logical expression that can be
represented as a tree. Besides its compactness, this universal
representation is also linear, and this is a fundamental characteristic
for any system that has to breed mathematical expressions to create new,
more precise ones....
