@article{nachbar:1995,
	title = {Genetic Programming},
	address = {600 Harrison st., San Francisco, CA 94107, USA},
	author = {Robert B. Nachbar},
	journal = {The Mathematica Journal},
	number = {3},
	pages = {44--55},
	publisher = {Miller Freedman Inc},
	url = {http://www.mathematica-journal.com/issue/v5i3/tutorials/nachbar/index.html},
	volume = {5},
	year = {1995},
	biburl = {http://www.bibsonomy.org/bibtex/2d72837366cb5f3c51360e508dd1b32e2/brazovayeye},
	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.},
	notes = {Tutorial. Mathemetica can simplify GP S-expressions.
                 Constant pertubation (=fine tuning mutation?) Announced
                 in posting to GP list on Mon, 12 Jun 95 08:39:42 EDT
                 Code available?},
	keywords = {Mathematica algorithms, genetic programming, }
}