953 research outputs found
If players are sparse social dilemmas are too: Importance of percolation for evolution of cooperation
Spatial reciprocity is a well known tour de force of cooperation promotion. A
thorough understanding of the effects of different population densities is
therefore crucial. Here we study the evolution of cooperation in social
dilemmas on different interaction graphs with a certain fraction of vacant
nodes. We find that sparsity may favor the resolution of social dilemmas,
especially if the population density is close to the percolation threshold of
the underlying graph. Regardless of the type of the governing social dilemma as
well as particularities of the interaction graph, we show that under pairwise
imitation the percolation threshold is a universal indicator of how dense the
occupancy ought to be for cooperation to be optimally promoted. We also
demonstrate that myopic updating, due to the lack of efficient spread of
information via imitation, renders the reported mechanism dysfunctional, which
in turn further strengthens its foundations.Comment: 6 two-column pages, 5 figures; accepted for publication in Scientific
Reports [related work available at http://arxiv.org/abs/1205.0541
Tuning the average path length of complex networks and its influence to the emergent dynamics of the majority-rule model
We show how appropriate rewiring with the aid of Metropolis Monte Carlo
computational experiments can be exploited to create network topologies
possessing prescribed values of the average path length (APL) while keeping the
same connectivity degree and clustering coefficient distributions. Using the
proposed rewiring rules we illustrate how the emergent dynamics of the
celebrated majority-rule model are shaped by the distinct impact of the APL
attesting the need for developing efficient algorithms for tuning such network
characteristics.Comment: 10 figure
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
From Local to Global Dilemmas in Social Networks
Social networks affect in such a fundamental way the dynamics of the population they support that the global, population-wide behavior that one observes often bears no relation to the individual processes it stems from. Up to now, linking the global networked dynamics to such individual mechanisms has remained elusive. Here we study the evolution of cooperation in networked populations and let individuals interact via a 2-person Prisoner's Dilemma – a characteristic defection dominant social dilemma of cooperation. We show how homogeneous networks transform a Prisoner's Dilemma into a population-wide evolutionary dynamics that promotes the coexistence between cooperators and defectors, while heterogeneous networks promote their coordination. To this end, we define a dynamic variable that allows us to track the self-organization of cooperators when co-evolving with defectors in networked populations. Using the same variable, we show how the global dynamics — and effective dilemma — co-evolves with the motifs of cooperators in the population, the overall emergence of cooperation depending sensitively on this co-evolution
Asymmetric evolutionary games
Evolutionary game theory is a powerful framework for studying evolution in
populations of interacting individuals. A common assumption in evolutionary
game theory is that interactions are symmetric, which means that the players
are distinguished by only their strategies. In nature, however, the microscopic
interactions between players are nearly always asymmetric due to environmental
effects, differing baseline characteristics, and other possible sources of
heterogeneity. To model these phenomena, we introduce into evolutionary game
theory two broad classes of asymmetric interactions: ecological and genotypic.
Ecological asymmetry results from variation in the environments of the players,
while genotypic asymmetry is a consequence of the players having differing
baseline genotypes. We develop a theory of these forms of asymmetry for games
in structured populations and use the classical social dilemmas, the Prisoner's
Dilemma and the Snowdrift Game, for illustrations. Interestingly, asymmetric
games reveal essential differences between models of genetic evolution based on
reproduction and models of cultural evolution based on imitation that are not
apparent in symmetric games.Comment: accepted for publication in PLOS Comp. Bio
Evolutionary establishment of moral and double moral standards through spatial interactions
Situations where individuals have to contribute to joint efforts or share
scarce resources are ubiquitous. Yet, without proper mechanisms to ensure
cooperation, the evolutionary pressure to maximize individual success tends to
create a tragedy of the commons (such as over-fishing or the destruction of our
environment). This contribution addresses a number of related puzzles of human
behavior with an evolutionary game theoretical approach as it has been
successfully used to explain the behavior of other biological species many
times, from bacteria to vertebrates. Our agent-based model distinguishes
individuals applying four different behavioral strategies: non-cooperative
individuals ("defectors"), cooperative individuals abstaining from punishment
efforts (called "cooperators" or "second-order free-riders"), cooperators who
punish non-cooperative behavior ("moralists"), and defectors, who punish other
defectors despite being non-cooperative themselves ("immoralists"). By
considering spatial interactions with neighboring individuals, our model
reveals several interesting effects: First, moralists can fully eliminate
cooperators. This spreading of punishing behavior requires a segregation of
behavioral strategies and solves the "second-order free-rider problem". Second,
the system behavior changes its character significantly even after very long
times ("who laughs last laughs best effect"). Third, the presence of a number
of defectors can largely accelerate the victory of moralists over non-punishing
cooperators. Forth, in order to succeed, moralists may profit from immoralists
in a way that appears like an "unholy collaboration". Our findings suggest that
the consideration of punishment strategies allows to understand the
establishment and spreading of "moral behavior" by means of game-theoretical
concepts. This demonstrates that quantitative biological modeling approaches
are powerful even in domains that have been addressed with non-mathematical
concepts so far. The complex dynamics of certain social behaviors becomes
understandable as result of an evolutionary competition between different
behavioral strategies.Comment: 15 pages, 5 figures; accepted for publication in PLoS Computational
Biology [supplementary material available at
http://www.soms.ethz.ch/research/secondorder-freeriders/ and
http://www.matjazperc.com/plos/moral.html
- …