z-logo
open-access-imgOpen Access
Calculating Evolutionary Dynamics in Structured Populations
Author(s) -
Charles Nathanson,
Corina E. Tarnita,
Martin A. Nowak
Publication year - 2009
Publication title -
plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1000615
Subject(s) - evolutionary dynamics , evolutionary game theory , context (archaeology) , population , evolutionary algorithm , outcome (game theory) , set (abstract data type) , selection (genetic algorithm) , core (optical fiber) , class (philosophy) , evolutionarily stable strategy , fitness landscape , computer science , limit (mathematics) , game theory , mathematical economics , mathematical optimization , mathematics , artificial intelligence , biology , demography , sociology , paleontology , telecommunications , mathematical analysis , programming language
Evolution is shaping the world around us. At the core of every evolutionary process is a population of reproducing individuals. The outcome of an evolutionary process depends on population structure. Here we provide a general formula for calculating evolutionary dynamics in a wide class of structured populations. This class includes the recently introduced “games in phenotype space” and “evolutionary set theory.” There can be local interactions for determining the relative fitness of individuals, but we require global updating, which means all individuals compete uniformly for reproduction. We study the competition of two strategies in the context of an evolutionary game and determine which strategy is favored in the limit of weak selection. We derive an intuitive formula for the structure coefficient, σ, and provide a method for efficient numerical calculation.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom