56,988 research outputs found
Complex Networks and Symmetry II: Reciprocity and Evolution of World Trade
We exploit the symmetry concepts developed in the companion review of this
article to introduce a stochastic version of link reversal symmetry, which
leads to an improved understanding of the reciprocity of directed networks. We
apply our formalism to the international trade network and show that a strong
embedding in economic space determines particular symmetries of the network,
while the observed evolution of reciprocity is consistent with a symmetry
breaking taking place in production space. Our results show that networks can
be strongly affected by symmetry-breaking phenomena occurring in embedding
spaces, and that stochastic network symmetries can successfully suggest, or
rule out, possible underlying mechanisms.Comment: Final accepted versio
Interdependent network reciprocity in evolutionary games
Besides the structure of interactions within networks, also the interactions between networks are of the outmost
importance. We therefore study the outcome of the public goods game on two interdependent networks that are
connected by means of a utility function, which determines how payoffs on both networks jointly influence the
success of players in each individual network. We show that an unbiased coupling allows the spontaneous
emergence of interdependent network reciprocity, which is capable to maintain healthy levels of public
cooperation even in extremely adverse conditions. The mechanism, however, requires simultaneous formation of
correlated cooperator clusters on both networks. If this does not emerge or if the coordination process is
disturbed, network reciprocity fails, resulting in the total collapse of cooperation. Network interdependence can
thus be exploited effectively to promote cooperation past the limits imposed by isolated networks, but only if the
coordination between the interdependent networks is not disturbe
Optimal distribution of incentives for public cooperation in heterogeneous interaction environments
In the framework of evolutionary games with institutional reciprocity,
limited incentives are at disposal for rewarding cooperators and punishing
defectors. In the simplest case, it can be assumed that, depending on their
strategies, all players receive equal incentives from the common pool. The
question arises, however, what is the optimal distribution of institutional
incentives? How should we best reward and punish individuals for cooperation to
thrive? We study this problem for the public goods game on a scale-free
network. We show that if the synergetic effects of group interactions are weak,
the level of cooperation in the population can be maximized simply by adopting
the simplest "equal distribution" scheme. If synergetic effects are strong,
however, it is best to reward high-degree nodes more than low-degree nodes.
These distribution schemes for institutional rewards are independent of payoff
normalization. For institutional punishment, however, the same optimization
problem is more complex, and its solution depends on whether absolute or
degree-normalized payoffs are used. We find that degree-normalized payoffs
require high-degree nodes be punished more lenient than low-degree nodes.
Conversely, if absolute payoffs count, then high-degree nodes should be
punished stronger than low-degree nodes.Comment: 19 pages, 8 figures; accepted for publication in Frontiers in
Behavioral Neuroscienc
Short versus long term benefits and the evolution of cooperation in the prisoner's dilemma game
In this paper I investigate the evolution of cooperation in the prisoner's dilemma when individuals change their strategies subject to performance evaluation of their neighbours over variable time horizons. In the monochrome setting, in which all agents per default share the same performance evaluation rule, weighing past events strongly dramatically enhances the prevalence of cooperators. For co-evolutionary models, in which evaluation time horizons and strategies can co-evolve, I demonstrate that cooperation naturally associates with long-term evaluation of others while defection is typically paired with very short time horizons. Moreover, considering the continuous spectrum in between enhanced and discounted weights of past performance, cooperation is optimally supported when cooperators neither give enhanced weight to past nor more recent events, but simply average payoffs. Payoff averaging is also found to emerge as the dominant strategy for cooperators in co-evolutionary models, thus proposing a natural route to the evolution of cooperation in viscous populations
Coveting thy neighbors fitness as a means to resolve social dilemmas
In spatial evolutionary games the fitness of each individual is traditionally
determined by the payoffs it obtains upon playing the game with its neighbors.
Since defection yields the highest individual benefits, the outlook for
cooperators is gloomy. While network reciprocity promotes collaborative
efforts, chances of averting the impending social decline are slim if the
temptation to defect is strong. It is therefore of interest to identify viable
mechanisms that provide additional support for the evolution of cooperation.
Inspired by the fact that the environment may be just as important as
inheritance for individual development, we introduce a simple switch that
allows a player to either keep its original payoff or use the average payoff of
all its neighbors. Depending on which payoff is higher, the influence of either
option can be tuned by means of a single parameter. We show that, in general,
taking into account the environment promotes cooperation. Yet coveting the
fitness of one's neighbors too strongly is not optimal. In fact, cooperation
thrives best only if the influence of payoffs obtained in the traditional way
is equal to that of the average payoff of the neighborhood. We present results
for the prisoner's dilemma and the snowdrift game, for different levels of
uncertainty governing the strategy adoption process, and for different
neighborhood sizes. Our approach outlines a viable route to increased levels of
cooperative behavior in structured populations, but one that requires a
thoughtful implementation.Comment: 10 two-column pages, 5 figures; accepted for publication in Journal
of Theoretical Biolog
Correlation of Positive and Negative Reciprocity Fails to Confer an Evolutionary Advantage: Phase Transitions to Elementary Strategies
Economic experiments reveal that humans value cooperation and fairness. Punishing unfair behavior is therefore common, and according to the theory of strong reciprocity, it is also directly related to rewarding cooperative behavior. However, empirical data fail to confirm that positive and negative reciprocity are correlated. Inspired by this disagreement, we determine whether the combined application of reward and punishment is evolutionarily advantageous. We study a spatial public goods game, where in addition to the three elementary strategies of defection, rewarding, and punishment, a fourth strategy that combines the latter two competes for space. We find rich dynamical behavior that gives rise to intricate phase diagrams where continuous and discontinuous phase transitions occur in succession. Indirect territorial competition, spontaneous emergence of cyclic dominance, as well as divergent fluctuations of oscillations that terminate in an absorbing phase are observed. Yet, despite the high complexity of solutions, the combined strategy can survive only in very narrow and unrealistic parameter regions. Elementary strategies, either in pure or mixed phases, are much more common and likely to prevail. Our results highlight the importance of patterns and structure in human cooperation, which should be considered in future experiments
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