Can quantitative and population genetics help us understand evolutionary computation? Conference Paper


Author(s): Barton, Nicholas H; Paixão, Tiago
Title: Can quantitative and population genetics help us understand evolutionary computation?
Affiliation IST Austria
Abstract: Even though both population and quantitative genetics, and evolutionary computation, deal with the same questions, they have developed largely independently of each other. I review key results from each field, emphasising those that apply independently of the (usually unknown) relation between genotype and phenotype. The infinitesimal model provides a simple framework for predicting the response of complex traits to selection, which in biology has proved remarkably successful. This allows one to choose the schedule of population sizes and selection intensities that will maximise the response to selection, given that the total number of individuals realised, C = ∑t Nt, is constrained. This argument shows that for an additive trait (i.e., determined by the sum of effects of the genes), the optimum population size and the maximum possible response (i.e., the total change in trait mean) are both proportional to √C.
Conference Title: GECCO: Genetic and evolutionary computation conference
Conference Dates: July 6-10, 2013
Conference Location: Amsterdam, Netherlands
ISBN: 978-1-4503-1963-8
Publisher: ACM  
Date Published: 2013-07-01
Start Page: 1573
End Page: 1580
Sponsor: This work was supported by ERC Advanced Grant ERC-2009-AdG-250152 SELECTIONINFORMATION.
URL:
DOI: 10.1145/2463372.2463568
Notes: The authors would like to thank the reviewers for their helpful comments.
Open access: yes (repository)
IST Austria Authors
  1. Nick Barton
    252 Barton
  2. Tiago Paixão
    27 Paixão
Related IST Austria Work