title: Guidelines: From artificial evolution to computational evolution: a research agenda.
abstract: Computational scientists have developed algorithms inspired by natural evolution for at least 50 years. These algorithms solve optimization and design problems by building solutions that are 'more fit' relative to desired properties. However, the basic assumptions of this approach are outdated. We propose a research programme to develop a new field: computational evolution. This approach will produce algorithms that are based on current understanding of molecular and evolutionary biology and could solve previously unimaginable or intractable computational and biological problems.
authors.affiliation: Department of Computer Science, Memorial University of Newfoundland, St John's, Newfoundland and Labrador A1B 3X5, Canada. banzhaf@cs.mun.ca
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Banzhaf
authors.forename: Guillaume
authors.initials: G
authors.lastname: Beslon
authors.forename: Steffen
authors.initials: S
authors.lastname: Christensen
authors.forename: James A
authors.initials: JA
authors.lastname: Foster
authors.forename: François
authors.initials: F
authors.lastname: Képès
authors.forename: Virginie
authors.initials: V
authors.lastname: Lefort
authors.forename: Julian F
authors.initials: JF
authors.lastname: Miller
authors.forename: Miroslav
authors.initials: M
authors.lastname: Radman
authors.forename: Jeremy J
authors.initials: JJ
authors.lastname: Ramsden
mesh_terms: D000465:Algorithms; D005075:Biological Evolution; D019295:Computational Biology; D017753:Ecosystem; D005823:Genetics; D005838:Genotype; D010641:Phenotype; D012106:Research