The Almost Sure Evolution of Hierarchy Among Similar Competitors

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Autori principali: Cebra, Christopher, Strang, Alexander
Natura: Preprint
Pubblicazione: 2024
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author Cebra, Christopher
Strang, Alexander
author_facet Cebra, Christopher
Strang, Alexander
contents While generic competitive systems exhibit mixtures of hierarchy and cycles, real-world systems are predominantly hierarchical. We demonstrate and extend a mechanism for hierarchy; systems with similar agents approach perfect hierarchy in expectation. A variety of evolutionary mechanisms plausibly select for nearly homogeneous populations, however, extant work does not explicitly link selection dynamics to hierarchy formation via population concentration. Moreover, previous work lacked numerical demonstration. This paper contributes in four ways. First, populations that converge to perfect hierarchy in expectation converge to hierarchy in probability. Second, we analyze hierarchy formation in populations subject to the continuous replicator dynamic with diffusive exploration, linking population dynamics to emergent structure. Third, we show how to predict the degree of cyclicity sustained by concentrated populations at internal equilibria. This theory can differentiate learning rules and random payout models. Finally, we provide direct numerical evidence by simulating finite populations of agents subject to a modified Moran process with Gaussian exploration. As examples, we consider three bimatrix games and an ensemble of games with random payouts. Through this analysis, we explicitly link the temporal dynamics of a population undergoing selection to the development of hierarchy.
format Preprint
id arxiv_https___arxiv_org_abs_2402_06005
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle The Almost Sure Evolution of Hierarchy Among Similar Competitors
Cebra, Christopher
Strang, Alexander
Populations and Evolution
Dynamical Systems
35Q89, 91-10, 92D15
While generic competitive systems exhibit mixtures of hierarchy and cycles, real-world systems are predominantly hierarchical. We demonstrate and extend a mechanism for hierarchy; systems with similar agents approach perfect hierarchy in expectation. A variety of evolutionary mechanisms plausibly select for nearly homogeneous populations, however, extant work does not explicitly link selection dynamics to hierarchy formation via population concentration. Moreover, previous work lacked numerical demonstration. This paper contributes in four ways. First, populations that converge to perfect hierarchy in expectation converge to hierarchy in probability. Second, we analyze hierarchy formation in populations subject to the continuous replicator dynamic with diffusive exploration, linking population dynamics to emergent structure. Third, we show how to predict the degree of cyclicity sustained by concentrated populations at internal equilibria. This theory can differentiate learning rules and random payout models. Finally, we provide direct numerical evidence by simulating finite populations of agents subject to a modified Moran process with Gaussian exploration. As examples, we consider three bimatrix games and an ensemble of games with random payouts. Through this analysis, we explicitly link the temporal dynamics of a population undergoing selection to the development of hierarchy.
title The Almost Sure Evolution of Hierarchy Among Similar Competitors
topic Populations and Evolution
Dynamical Systems
35Q89, 91-10, 92D15
url https://arxiv.org/abs/2402.06005