- author = "Darrell Whitley and Marc Richards and Ross Beveridge and Andre' {da Motta Salles Barreto}",
- title = "Alternative evolutionary algorithms for evolving programs: evolution strategies and steady state {GP}",
- booktitle = "{GECCO 2006:} Proceedings of the 8th annual conference on Genetic and evolutionary computation",
- year = "2006",
- editor = "Maarten Keijzer and Mike Cattolico and Dirk Arnold and Vladan Babovic and Christian Blum and Peter Bosman and Martin V. Butz and Carlos {Coello Coello} and Dipankar Dasgupta and Sevan G. Ficici and James Foster and Arturo Hernandez-Aguirre and Greg Hornby and Hod Lipson and Phil McMinn and Jason Moore and Guenther Raidl and Franz Rothlauf and Conor Ryan and Dirk Thierens",
- volume = "1",
- ISBN = "1-59593-186-4",
- pages = "919--926",
- address = "Seattle, Washington, USA",
-
URL = "
http://gpbib.cs.ucl.ac.uk/gecco2006/docs/p919.pdf",
-
DOI = "
doi:10.1145/1143997.1144155",
- publisher = "ACM Press",
- publisher_address = "New York, NY, 10286-1405, USA",
- month = "8-12 " # jul,
- organisation = "ACM SIGEVO (formerly ISGEC)",
- keywords = "genetic algorithms, genetic programming, evolution strategies, ES, steady-state genetic algorithms, Automatic Programming, Program Synthesis",
- size = "8 pages",
- abstract = "In contrast with the diverse array of genetic algorithms, the Genetic Programming (GP) paradigm is usually applied in a relatively uniform manner. Heuristics have developed over time as to which replacement strategies and selection methods are best. The question addressed in this paper is relatively simple: since there are so many variants of evolutionary algorithm, how well do some of the other well known forms of evolutionary algorithm perform when used to evolve programs trees using s-expressions as the representation? Our results suggest a wide range of evolutionary algorithms are all equally good at evolving programs, including the simplest evolution strategies",
-
notes = "GECCO-2006 A joint meeting of the fifteenth
international conference on genetic algorithms
(ICGA-2006) and the eleventh annual genetic programming
conference (GP-2006).
ACM Order Number 910060
Winner best paper.",
