Emergent kin selection of altruistic feeding via non-episodic neuroevolution

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Main Authors: Taylor-Davies, Max, Hamon, Gautier, Boulet, Timothé, Moulin-Frier, Clément
Format: Preprint
Published: 2024
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author Taylor-Davies, Max
Hamon, Gautier
Boulet, Timothé
Moulin-Frier, Clément
author_facet Taylor-Davies, Max
Hamon, Gautier
Boulet, Timothé
Moulin-Frier, Clément
contents Kin selection theory has proven to be a popular and widely accepted account of how altruistic behaviour can evolve under natural selection. Hamilton's rule, first published in 1964, has since been experimentally validated across a range of different species and social behaviours. In contrast to this large body of work in natural populations, however, there has been relatively little study of kin selection \emph{in silico}. In the current work, we offer what is to our knowledge the first demonstration of kin selection emerging naturally within a population of agents undergoing continuous neuroevolution. Specifically, we find that zero-sum transfer of resources from parents to their infant offspring evolves through kin selection in environments where it is hard for offspring to survive alone. In an additional experiment, we show that kin selection in our simulations relies on a combination of kin recognition and population viscosity. We believe that our work may contribute to the understanding of kin selection in minimal evolutionary systems, without explicit notions of genes and fitness maximisation.
format Preprint
id arxiv_https___arxiv_org_abs_2411_10536
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Emergent kin selection of altruistic feeding via non-episodic neuroevolution
Taylor-Davies, Max
Hamon, Gautier
Boulet, Timothé
Moulin-Frier, Clément
Populations and Evolution
Neural and Evolutionary Computing
Kin selection theory has proven to be a popular and widely accepted account of how altruistic behaviour can evolve under natural selection. Hamilton's rule, first published in 1964, has since been experimentally validated across a range of different species and social behaviours. In contrast to this large body of work in natural populations, however, there has been relatively little study of kin selection \emph{in silico}. In the current work, we offer what is to our knowledge the first demonstration of kin selection emerging naturally within a population of agents undergoing continuous neuroevolution. Specifically, we find that zero-sum transfer of resources from parents to their infant offspring evolves through kin selection in environments where it is hard for offspring to survive alone. In an additional experiment, we show that kin selection in our simulations relies on a combination of kin recognition and population viscosity. We believe that our work may contribute to the understanding of kin selection in minimal evolutionary systems, without explicit notions of genes and fitness maximisation.
title Emergent kin selection of altruistic feeding via non-episodic neuroevolution
topic Populations and Evolution
Neural and Evolutionary Computing
url https://arxiv.org/abs/2411.10536