Choosing Fitness-Enhancing Innovations Can Be Detrimental under Fluctuating Environments
Author(s) -
Julian Z. Xue,
André Costopoulos,
Frédéric Guichard
Publication year - 2011
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.0026770
Subject(s) - genetic fitness , adaptation (eye) , mechanism (biology) , fitness landscape , survival of the fittest , inheritance (genetic algorithm) , inclusive fitness , population , computer science , extinction (optical mineralogy) , term (time) , selection (genetic algorithm) , biology , evolutionary biology , artificial intelligence , genetics , demography , philosophy , paleontology , physics , epistemology , quantum mechanics , neuroscience , sociology , gene
The ability to predict the consequences of one's behavior in a particular environment is a mechanism for adaptation. In the absence of any cost to this activity, we might expect agents to choose behaviors that maximize their fitness, an example of directed innovation. This is in contrast to blind mutation, where the probability of becoming a new genotype is independent of the fitness of the new genotypes. Here, we show that under environments punctuated by rapid reversals, a system with both genetic and cultural inheritance should not always maximize fitness through directed innovation. This is because populations highly accurate at selecting the fittest innovations tend to over-fit the environment during its stable phase, to the point that a rapid environmental reversal can cause extinction. A less accurate population, on the other hand, can track long term trends in environmental change, keeping closer to the time-average of the environment. We use both analytical and agent-based models to explore when this mechanism is expected to occur.
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