
networks and genetic algorithms, play a relatively minor role in GP im-
plementations. The selection of the function and terminal sets sig-
nificantly depends on the problem domain, however, so this selection
could be thought of as preprocessing.
Formulating the approach to solving a problem with a GP implemen-
tation can be difficult. Discovering what other people have done in simi-
lar circumstances is often helpful. Chapter 26 of Koza’s 1992 book pre-
sents tables to help guide a user in selection of terminal sets, function
sets, population size, and so on. Genetic programming has, as have the
other evolutionary algorithms we’ve discussed, developed ...