Article,
Genetic Programming
The Mathematica Journal, 5 (3): 44--55 (1995)
Abstract
This article presents a method for optimizing
expressions to solve a given problem using the strategy
of Darwinism. In contrast to genetic algorithms, which
evolve an encoded representation of the solution,
genetic programming evolves the solution expression
directly. The Mathematica implementation makes use of
the built-in features of functional programming,
recursion, and hierarchical data structures. An
application to symbolic regression is presented.
