- author = "Conor Ryan and Michael O'Neill",
- title = "Grammatical Evolution: A Steady State approach",
- booktitle = "Late Breaking Papers at the Genetic Programming 1998 Conference",
- year = "1998",
- editor = "John R. Koza",
- pages = "180--185",
- address = "University of Wisconsin, Madison, Wisconsin, USA",
- publisher_address = "Stanford, CA, USA",
- month = "22-25 " # jul,
- publisher = "Stanford University Bookstore",
- keywords = "genetic algorithms, genetic programming, grammatical evolution",
-
URL = "
http://citeseer.ist.psu.edu/cache/papers/cs/12751/http:zSzzSzscare.csis.ul.iezSzmichaelzSzpaperszSzgp98.pdf/ryan98grammatical.pdf",
-
URL = "
http://citeseer.ist.psu.edu/260828.html",
-
URL = "http://www.grammatical-evolution.org/papers/gp98/index.html",
- size = "6 pages",
-
abstract = "We describe a Genetic Algorithm that can evolve
complete programs. Using a variable length linear
genome to govern the mapping of a Backus Naur Form
grammar definition to a program, expressions and
programs of arbitrary complexity may be evolved. Our
system, Grammatical Evolution, has been applied to
problems such as a Symbolic Regression problem, and
finding Trigonometric Identities.
In this paper we describe how we applied GE to a Symbolic Integration problem, that being finding a function which is an integral of Cos(X)+2X+1. We also show how a Steady State selection mechanism was found to improve the performance of Grammatical Evolution.",
- notes = "GP-98LB",
