Evolving division of labor in a response threshold model

Fuente: arXiv
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Autori principali: Fontanari, José F., de Oliveira, Viviane M., Campos, Paulo R. A.
Natura: Preprint
Pubblicazione: 2023
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author Fontanari, José F.
de Oliveira, Viviane M.
Campos, Paulo R. A.
author_facet Fontanari, José F.
de Oliveira, Viviane M.
Campos, Paulo R. A.
contents The response threshold model explains the emergence of division of labor (i.e., task specialization) in an unstructured population by assuming that the individuals have different propensities to work on different tasks. The incentive to attend to a particular task increases when the task is left unattended and decreases when individuals work on it. Here we derive mean-field equations for the stimulus dynamics and show that they exhibit complex attractors through period-doubling bifurcation cascades when the noise disrupting the thresholds is small. In addition, we show how the fixed threshold can be set to ensure specialization in both the transient and equilibrium regimes of the stimulus dynamics. However, a complete explanation of the emergence of division of labor requires that we address the question of where the threshold variation comes from, starting from a homogeneous population. We then study a structured population scenario, where the population is divided into a large number of independent groups of equal size, and the fitness of a group is proportional to the weighted mean work performed on the tasks during a fixed period of time. Using a winner-take-all strategy to model group competition and assuming an initial homogeneous metapopulation, we find that a substantial fraction of workers specialize in each task, without the need to penalize task switching.
format Preprint
id arxiv_https___arxiv_org_abs_2308_07122
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Evolving division of labor in a response threshold model
Fontanari, José F.
de Oliveira, Viviane M.
Campos, Paulo R. A.
Populations and Evolution
Adaptation and Self-Organizing Systems
Chaotic Dynamics
The response threshold model explains the emergence of division of labor (i.e., task specialization) in an unstructured population by assuming that the individuals have different propensities to work on different tasks. The incentive to attend to a particular task increases when the task is left unattended and decreases when individuals work on it. Here we derive mean-field equations for the stimulus dynamics and show that they exhibit complex attractors through period-doubling bifurcation cascades when the noise disrupting the thresholds is small. In addition, we show how the fixed threshold can be set to ensure specialization in both the transient and equilibrium regimes of the stimulus dynamics. However, a complete explanation of the emergence of division of labor requires that we address the question of where the threshold variation comes from, starting from a homogeneous population. We then study a structured population scenario, where the population is divided into a large number of independent groups of equal size, and the fitness of a group is proportional to the weighted mean work performed on the tasks during a fixed period of time. Using a winner-take-all strategy to model group competition and assuming an initial homogeneous metapopulation, we find that a substantial fraction of workers specialize in each task, without the need to penalize task switching.
title Evolving division of labor in a response threshold model
topic Populations and Evolution
Adaptation and Self-Organizing Systems
Chaotic Dynamics
url https://arxiv.org/abs/2308.07122