@conference { andre:1996:GKL,
	title = {Evolution of Intricate Long-Distance Communication Signals in Cellular Automata using Genetic Programming},
	volume = {1},
	year = {1996},
	month = {"16--18 " # may},
	publisher = {MIT Press},
	type = {inproceedings},
	address = {Nara, Japan},
	abstract = {A cellular automata rule for the majority
                 classification task was evolved using genetic
                 programming with automatically defined functions. The
                 genetically evolved rule has an accuracy of 82.326%.
                 This level of accuracy exceeds that of the
                 Gacs-Kurdyumov-Levin (GKL) rule, all other known
                 human-written rules, and all other rules produced by
                 known previous automated approaches.

                 Our genetically evolved rule is qualitatively different
                 from other rules in that it uses a fine-grained
                 internal representation of density information; it
                 employs a large number of different domains and
                 particles; and it uses an intricate set of signals for
                 communicating information over large distances in time
                 and space.},
	keywords = {genetic algorithms, genetic programming},
	URL = {http://www.genetic-programming.com/jkpdf/alife1996gkl.pdf},
	author = { Andre, David  and  III, Forrest H Bennett  and  Koza, John R.}
}