Volume 113, Number 5, March 2016
|Number of page(s)||6|
|Section||Interdisciplinary Physics and Related Areas of Science and Technology|
|Published online||31 March 2016|
Collective influence in evolutionary social dilemmas
1 Institute of Technical Physics and Materials Science, Centre for Energy Research, Hungarian Academy of Sciences P.O. Box 49, H-1525 Budapest, Hungary
2 Faculty of Natural Sciences and Mathematics, University of Maribor - Koroška cesta 160, SI-2000 Maribor, Slovenia
3 CAMTP – Center for Applied Mathematics and Theoretical Physics, University of Maribor Krekova 2, SI-2000 Maribor, Slovenia
Received: 3 January 2016
Accepted: 24 March 2016
When evolutionary games are contested in structured populations, the degree of each player in the network plays an important role. If they exist, hubs often determine the fate of the population in remarkable ways. Recent research based on optimal percolation in random networks has shown, however, that the degree is neither the sole nor the best predictor of influence in complex networks. Low-degree nodes may also be optimal influencers if they are hierarchically linked to hubs. Taking this into account leads to the formalism of collective influence in complex networks, which as we show here, has far-reaching implications for the favorable resolution of social dilemmas. In particular, there exists an optimal hierarchical depth for the determination of collective influence that we use to describe the potency of players for passing their strategies, which depends on the strength of the social dilemma. Interestingly, the degree, which corresponds to the baseline depth zero, is optimal only when the temptation to defect is small. Our research reveals that evolutionary success stories are related to spreading processes which are rooted in favorable hierarchical structures that extend beyond local neighborhoods.
PACS: 87.23.Kg – Dynamics of evolution / 87.23.Cc – Population dynamics and ecological pattern formation / 89.65.-s – Social and economic systems
© EPLA, 2016
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