Cooperative behaviour is widespread in nature, but explaining how cooperation evolves constitutes a major scientific challenge. Simulation models has shown that social network structure plays a key role in rendering cooperationevolutionarily stable . However, not much is known about the importance of initial conditions for the evolution of cooperation in networks. Knowledge about this is essential for judging to which extent results from modelling and experiments can tell us something about the real world. Here, we investigate how cooperation is affected by the initial network positions of cooperators in different networks, by means of game-theory based simulation models. We find that placing cooperators on  high-degree nodes enhances cooperationin standard scale-free networks but not in standard Poisson networks. In contrast, under increased degree assortativity , Poisson networks can maintain high levels of cooperation, even exceeding those of scale-free networks, when the initial placement of cooperators is perfectly correlated to node degree. When the correlation is not perfect however, defectors placed within clusters of cooperators can act as Trojan horses, allowing defection to invade. The results are relevant both to computer simulations of cooperation in networks and in particular to real-world cooperation experiments, where the number of replications is typically low and stochastic initial correlations between cooperativeness and network position may be present .
Cooperative behaviour is widespread in nature, but explaining how cooperation evolves constitutes a major scientific challenge. Computer simulations have shown that social network structure plays a key role for the viability of cooperation . However, not much is known about the importance of correlations between cooperative strategy and network position for the evolution of cooperation . Here, we investigate how cooperation is affected by correlations between cooperative strategy and individual connectedness in different networks, by means of simulation models. We find that placing cooperators on well-connected ( high-degree ) nodes can - as expected - enhance cooperation , but will only do so under certain conditions. The effect depends nontrivially on the combination of the social network structure (degree distribution and assortativity), the type of social dilemma, and the presence of Trojan horses, i.e. defectors placed within clusters of cooperators . Interestingly, the largest enhancement is observed in Poisson networks with increased degree assortativity, where cooperation does better than under scale-free degree distribution. The study provides new knowledge about the conditions under which cooperation may evolve and persist. The results are furthermore important to consider in regard to cooperation experiments, as they imply that stochastic initial correlations between cooperativeness and network position can affect the results of such experiments .
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in rendering cooperationevolutionarily stable
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in networks. Knowledge about this is essential for judging to which extent results from modelling and experiments can tell us something about the real world.
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the initial network positions of cooperators
correlations between cooperative strategy and individual connectedness
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game-theory based
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well-connected (
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nodes enhances cooperationin standard scale-free networks but not in standard Poisson networks. In contrast, under increased degree assortativity
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Poisson networks can maintain high levels of cooperation, even exceeding those of scale-free networks, when the initial placement of cooperators is perfectly correlated to node degree. When the correlation is not perfect however,
but will only do so under certain conditions. The effect depends nontrivially on the combination of the social network structure (degree distribution and assortativity), the type of social dilemma, and the presence of Trojan horses, i.e.
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can act as Trojan horses, allowing defection to invade. The results are relevant both to computer simulations of cooperation in networks and in particular to real-world
. Interestingly, the largest enhancement is observed in Poisson networks with increased degree assortativity, where cooperation does better than under scale-free degree distribution. The study provides new knowledge about the conditions under which cooperation may evolve and persist. The results are furthermore important to consider in regard to
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where the number of replications is typically low and
as they imply that
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may be present
can affect the results of such experiments