Evolution of public cooperation on interdependent networks: The impact of biased utility functions

By Zhen Wang, Attila Szolnoki, Matjaz Perc. arXiv.org, 2012

359 citations recorded by the source corpus.

We study the evolution of public cooperation on two interdependent networks that are connected by means of a utility function, which determines to what extent payoffs in one network influence the success of players in the other network. We find that the stronger the bias in the utility function, the higher the level of public cooperation. Yet the benefits of enhanced public cooperation on the two networks are just as biased as the utility functions themselves. While cooperation may thrive on one network, the other may still be plagued by defectors. Nevertheless, the aggregate level of cooperation on both networks is higher than the one attainable on an isolated network. This positive effect of biased utility functions is due to the suppressed feedback of individual success, which leads to a spontaneous separation of characteristic time scales of the evolutionary process on the two interdependent networks. As a result, cooperation is promoted because the aggressive invasion of defectors is more sensitive to the slowing-down than the build-up of collective efforts in sizable groups.

Subfields: Economics and Econometrics, Management Science and Operations Research, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/ef0cc8f56c8e9cbe204ad4dbe2b6a5bfb78a6408

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Management Science and Operations Research

In Sociology and Political Science

Citations in the corpus

Interdependent network reciprocity in evolutionary games (2013, background): “In general, within the realm of evolutionary games, it is mos t natural to assume that the interconnectedness will not allo w direct strategy exchanges between the networks, but rather ffect the utility function of players which influences the str ategy imitation probability within a network [12].”
Evolution of Cooperation in Multiplex Networks (2012, background): “However, the influence that the multiplex nature of social interactions has on the evolution of cooperation is still an open question, being recently tackled [39] within a framework consisting in two coupled networks.”
Evolutionary dynamics of group interactions on structured populations: a review (2013, background): “[108].”
Multilayer networks (2013, background): “, in a public-goods game in a coupled pair of square lattices [330,347,348]).”
The structure and dynamics of multilayer networks (2014, background): “[355] is that, when one layer almost dominates the other, cooperation is extraordinarily favored in the slave layer.”
Networks beyond pairwise interactions: structure and dynamics (2020, background): “While not making possible direct strategy exchanges between the networks, interconnectedness can affect the utility function of players, who do not have access to the earnings of their neighbors on each of the layers but only to a (possibly non-linear) combination of them [562].”