619 research outputs found
Self-organization towards optimally interdependent networks by means of coevolution
Coevolution between strategy and network structure is established as a means to arrive at the optimal conditions needed to resolve social dilemmas. Yet recent research has highlighted that the interdependence between networks may be just as important as the structure of an individual network. We therefore introduce the coevolution of strategy and network interdependence to see whether this can give rise to elevated levels of cooperation in the prisonerʼs dilemma game. We show that the interdependence between networks self-organizes so as to yield optimal conditions for the evolution of cooperation. Even under extremely adverse conditions, cooperators can prevail where on isolated networks they would perish. This is due to the spontaneous emergence of a two-class society, with only the upper class being allowed to control and take advantage of the interdependence. Spatial patterns reveal that cooperators, once arriving at the upper class, are much more competent than defectors in sustaining compact clusters of followers. Indeed, the asymmetric exploitation of interdependence confers to them a strong evolutionary advantage that may resolve even the toughest of social dilemmas
Topological enslavement in evolutionary games on correlated multiplex networks
Governments and enterprises strongly rely on incentives to generate favorable
outcomes from social and strategic interactions between individuals. The
incentives are usually modeled by payoffs in evolutionary games, such as the
prisoner's dilemma or the harmony game, with imitation dynamics. Adjusting the
incentives by changing the payoff parameters can favor cooperation, as found in
the harmony game, over defection, which prevails in the prisoner's dilemma.
Here, we show that this is not always the case if individuals engage in
strategic interactions in multiple domains. In particular, we investigate
evolutionary games on multiplex networks where individuals obtain an aggregate
payoff. We explicitly control the strength of degree correlations between nodes
in the different layers of the multiplex. We find that if the multiplex is
composed of many layers and degree correlations are strong, the topology of the
system enslaves the dynamics and the final outcome, cooperation or defection,
becomes independent of the payoff parameters. The fate of the system is then
determined by the initial conditions
Conformity enhances network reciprocity in evolutionary social dilemmas
The pursuit of highest payoffs in evolutionary social dilemmas is risky and
sometimes inferior to conformity. Choosing the most common strategy within the
interaction range is safer because it ensures that the payoff of an individual
will not be much lower than average. Herding instincts and crowd behavior in
humans and social animals also compel to conformity on their own right.
Motivated by these facts, we here study the impact of conformity on the
evolution of cooperation in social dilemmas. We show that an appropriate
fraction of conformists within the population introduces an effective surface
tension around cooperative clusters and ensures smooth interfaces between
different strategy domains. Payoff-driven players brake the symmetry in favor
of cooperation and enable an expansion of clusters past the boundaries imposed
by traditional network reciprocity. This mechanism works even under the most
testing conditions, and it is robust against variations of the interaction
network as long as degree-normalized payoffs are applied. Conformity may thus
be beneficial for the resolution of social dilemmas.Comment: 8 two-column pages, 5 figures; accepted for publication in Journal of
the Royal Society Interfac
Evolutionary games on multilayer networks: A colloquium
Networks form the backbone of many complex systems, ranging from the Internet
to human societies. Accordingly, not only is the range of our interactions
limited and thus best described and modeled by networks, it is also a fact that
the networks that are an integral part of such models are often interdependent
or even interconnected. Networks of networks or multilayer networks are
therefore a more apt description of social systems. This colloquium is devoted
to evolutionary games on multilayer networks, and in particular to the
evolution of cooperation as one of the main pillars of modern human societies.
We first give an overview of the most significant conceptual differences
between single-layer and multilayer networks, and we provide basic definitions
and a classification of the most commonly used terms. Subsequently, we review
fascinating and counterintuitive evolutionary outcomes that emerge due to
different types of interdependencies between otherwise independent populations.
The focus is on coupling through the utilities of players, through the flow of
information, as well as through the popularity of different strategies on
different network layers. The colloquium highlights the importance of pattern
formation and collective behavior for the promotion of cooperation under
adverse conditions, as well as the synergies between network science and
evolutionary game theory.Comment: 14 two-column pages, 8 figures; accepted for publication in European
Physical Journal
Coupled dynamics of node and link states in complex networks: A model for language competition
Inspired by language competition processes, we present a model of coupled
evolution of node and link states. In particular, we focus on the interplay
between the use of a language and the preference or attitude of the speakers
towards it, which we model, respectively, as a property of the interactions
between speakers (a link state) and as a property of the speakers themselves (a
node state). Furthermore, we restrict our attention to the case of two socially
equivalent languages and to socially inspired network topologies based on a
mechanism of triadic closure. As opposed to most of the previous literature,
where language extinction is an inevitable outcome of the dynamics, we find a
broad range of possible asymptotic configurations, which we classify as: frozen
extinction states, frozen coexistence states, and dynamically trapped
coexistence states. Moreover, metastable coexistence states with very long
survival times and displaying a non-trivial dynamics are found to be abundant.
Interestingly, a system size scaling analysis shows, on the one hand, that the
probability of language extinction vanishes exponentially for increasing system
sizes and, on the other hand, that the time scale of survival of the
non-trivial dynamical metastable states increases linearly with the size of the
system. Thus, non-trivial dynamical coexistence is the only possible outcome
for large enough systems. Finally, we show how this coexistence is
characterized by one of the languages becoming clearly predominant while the
other one becomes increasingly confined to "ghetto-like" structures: small
groups of bilingual speakers arranged in triangles, with a strong preference
for the minority language, and using it for their intra-group interactions
while they switch to the predominant language for communications with the rest
of the population.Comment: 21 pages, 15 figure
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