20.500.12556/DKUM-90127 Identification of influential invaders in evolutionary populations The identification of the most influential nodes has been a vibrant subject of research across the whole of network science. Here we map this problem to structured evolutionary populations, where strategies and the interaction network are both subject to change over time based on social inheritance. We study cooperative communities, which cheaters can invade because they avoid the cost of contributions that are associated with cooperation. The question that we seek to answer is at which nodes cheaters invade most successfully. We propose the weighted degree decomposition to identify and rank the most influential invaders. More specifically, we distinguish two kinds of ranking based on the weighted degree decomposition. We show that a ranking strategy based on negative-weighted degree allows to successfully identify the most influential invaders in the case of weak selection, while a ranking strategy based on positive-weighted degree performs better when the selection is strong. Our research thus reveals how to identify the most influential invaders based on statistical measures in dynamically evolving cooperative communities. theoretical biology evolution agent-based modeling complex system network science evolutionary game theory teoretična biologija evolucija agentske simulacije kompleksni sistem omrežna znanost evolucijska teorija iger true false true Angleški jezik Slovenski jezik Znanstveno delo 2024-08-23 04:12:53 2025-02-26 10:21:41 2025-02-27 03:11:28 0000-00-00 00:00:00 2019 0 0 str. 1-12 št. članka 7305 Letn. 9 2019 0000-00-00 Zaloznikova Objavljeno apc 2019-01-30 2019-05-01 2019-05-13 53 24580360 10.1038/s41598-019-43853-9 2045-2322 RAZ_Yang_Guoli_2019.pdf RAZ_Yang_Guoli_2019.pdf 1 FC1ABD033446A5325CEDDD0BF621E461 3646310979d8cc7576cb9bc4ae13595d72cf90b0518e57a8c2982f8dc057b2b9 05d14e76-f423-11ef-a5fa-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=188838 https://doi.org/10.1038/s41598-019-43853-9 0 10196138-f423-11ef-a5fa-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=188839 Fakulteta za naravoslovje in matematiko 0 0 0