Skip to main content

Research Repository

Advanced Search

Testing the Variability Selection Hypothesis: The Adoption of Social Learning in Increasingly Variable Environments

Channon

Testing the Variability Selection Hypothesis: The Adoption of Social Learning in Increasingly Variable Environments Thumbnail


Authors



Abstract

The variability selection hypothesis predicts the adoption of versatile behaviors and survival strategies, in response to increasingly variable environments. In hominin evolution the most apparent adaptation for versatility is the adoption of social learning. The hypothesis that social learning will be adopted over other learning strategies, such as individual learning, when individuals are faced with increasingly variable environments is tested here using a genetic algorithm with steady state selection and constant population size. Individuals, constituted of binary string genotypes and phenotypes, are evaluated on their ability to match a target binary string, nominally known as the environment, with success being measured by the Hamming distance between the phenotype and environment. The state of any given locus in the environment is determined by a sine wave, the frequency of which increases as the simulation progresses thus providing increasing environmental variability. Populations exhibiting combinations of genetic evolution, individual learning and social learning are tested, with the learning rates of both individual and social learning allowed to evolve. We show that increasingly variable environments are sufficient but not necessary to provide an evolutionary advantage to those populations exhibiting the extra-genetic learning strategies, with social learning being favored over individual learning when populations are allowed to explore both strategies simultaneously. We also introduce a more biologically realistic model that allows for population collapse, and show that here the prior adoption of individual learning is a prerequisite for the successful adoption of social learning in increasingly variable environments.

Acceptance Date Jul 1, 2012
Publication Date Jul 1, 2012
Journal Artificial Life
Print ISSN 1064-5462
Publisher Massachusetts Institute of Technology Press
Pages 317 -324
Series Title Artificial Life XIII: The Thirteenth International Conference on the Simulation and Synthesis of Living Systems
DOI https://doi.org/10.7551/978-0-262-31050-5-ch042
Publisher URL https://doi.org/10.7551/978-0-262-31050-5-ch042

Files




You might also like



Downloadable Citations