Ranking the invasions of cheaters in structured populations.

Abstract:

:The identification of the most influential individuals in structured populations is an important research question, with many applications across the social and natural sciences. Here, we study this problem in evolutionary populations on static networks, where invading cheaters can lead to the collapse of cooperation. We propose six strategies to rank the invading cheaters and identify those which mostly facilitate the collapse of cooperation. We demonstrate that the type of successful rankings depend on the selection strength, the underlying game, and the network structure. We show that random ranking has generally little ability to successfully identify invading cheaters, especially for the stag-hunt game in scale-free networks and when the selection strength is strong. The ranking based on degree can successfully identify the most influential invaders when the selection strength is weak, while more structured rankings perform better at strong selection. Scale-free networks and strong selection are generally detrimental to the performance of the random ranking, but they are beneficial for the performance of structured rankings. Our research reveals how to identify the most influential invaders using statistical measures in structured communities, and it demonstrates how their success depends on population structure, selection strength, and on the underlying game dynamics.

journal_name

Sci Rep

journal_title

Scientific reports

authors

Yang G,Cavaliere M,Zhu C,Perc M

doi

10.1038/s41598-020-59020-4

subject

Has Abstract

pub_date

2020-02-10 00:00:00

pages

2231

issue

1

issn

2045-2322

pii

10.1038/s41598-020-59020-4

journal_volume

10

pub_type

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