Can quantitative and population genetics help us understand evolutionary computation?

Barton, Nicholas H and Paixão, Tiago (2013) Can quantitative and population genetics help us understand evolutionary computation? In: GECCO: Genetic and evolutionary computation conference, July 6-10, 2013, Amsterdam, Netherlands.

[img] Text
NickGECCO_2013_1_-1.pdf - Submitted Version
Available under License All rights reserved.
[IST-2016-564-v1+1]
Download (464Kb)
Official URL: http://dx.doi.org/10.1145/2463372.2463568

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.

Item Type: Conference or Workshop Item (Paper)
Additional Information: "© Barton, Nicholas H; Paixão, Tiago|2013. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in GECCO '13 Proceedings of the 15th annual conference on Genetic and evolutionary computation, http://dx.doi.org/10.1145/2463372.2463568}."
Subjects: 500 Science > 570 Life sciences; biology
Research Group: Barton Group
SWORD Depositor: Sword Import User
Depositing User: Nicholas Barton
Date Deposited: 11 May 2016 13:08
Last Modified: 05 Sep 2017 14:12
URI: https://repository.ist.ac.at/id/eprint/564

Actions (login required)

View Item View Item