Evolutionary game dynamics in a growing structured population
J. Poncela, J. Gómez-Gardeñes, Y. Moreno, A. TraulsenNEW JOURNAL OF PHYSICS 11, 083031 (2009)
Times cited: 78
Abstract
We discuss a model for evolutionary game dynamics in a growing,
network-structured population. In our model, new players can either
make
connections to random preexisting players or preferentially attach to
those
that have been successful in the past. The latter depends on the
dynamics of
strategies in the game, which we implement following the so-called Fermi
rule
such that the limits of weak and strong strategy selection can be
explored.
Our framework allows to address general evolutionary games. With only
two
parameters describing the preferential attachment and the intensity of
selection,
we describe a wide range of network structures and evolutionary
scenarios.
Our results show that even for moderate payoff preferential attachment,
over
represented hubs arise. Interestingly, we find that while the networks
are
growing, high levels of cooperation are attained, but the same network
structure
does not promote cooperation as a static network. Therefore, the
mechanism of
payoff preferential attachment is different to those usually invoked to
explain the
promotion of cooperation in static, already-grown networks.