Adaptive Topographies and Equilibrium Selection in an Evolutionary Game
Author(s) -
Hinke M. Osinga,
James A. R. Marshall
Publication year - 2015
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0116307
Subject(s) - evolutionary game theory , population , trait , game theory , equilibrium selection , selection (genetic algorithm) , evolutionary biology , locus (genetics) , population genetics , evolutionary dynamics , human evolutionary genetics , biology , mathematical economics , computer science , mathematics , genetics , repeated game , artificial intelligence , demography , genome , sociology , gene , programming language
It has long been known in the field of population genetics that adaptive topographies, in which population equilibria maximise mean population fitness for a trait regardless of its genetic bases, do not exist. Whether one chooses to model selection acting on a single locus or multiple loci does matter. In evolutionary game theory, analysis of a simple and general game involving distinct roles for the two players has shown that whether strategies are modelled using a single ‘locus’ or one ‘locus’ for each role, the stable population equilibria are unchanged and correspond to the fitness-maximising evolutionary stable strategies of the game. This is curious given the aforementioned population genetical results on the importance of the genetic bases of traits. Here we present a dynamical systems analysis of the game with roles detailing how, while the stable equilibria in this game are unchanged by the number of ‘loci’ modelled, equilibrium selection may differ under the two modelling approaches.
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