Open AccessBehavior of finite population variable length genetic algorithms under random selection
Author(s) -
Hal Stringer,
Annie S. Wu
Publication year - 2005
Publication title -
journal of international crisis and risk communication research
Language(s) - English
Resource type - Conference proceedings
eISSN - 2576-0025
pISSN - 2576-0017
ISBN - 1-59593-010-8
DOI - 10.1145/1068009.1068213
Subject(s) - selection (genetic algorithm) , genetic algorithm , population , variable (mathematics) , algorithm , chromosome , population size , feature selection , random variable , computer science , property (philosophy) , mathematics , statistics , mathematical optimization , biology , genetics , artificial intelligence , demography , philosophy , mathematical analysis , sociology , epistemology , gene
In this work we provide empirical evidence that shows how a variable-length genetic algorithm (GA) can naturally evolve shorter average size populations. This reduction in chromosome length appears to occur in finite population GAs when 1) selection is absent from the GA (random) or 2) when selection focuses on some other property not influenced by the length of individuals within a population.
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