36,191 research outputs found
Emergence of Cooperation in Non-scale-free Networks
Evolutionary game theory is one of the key paradigms behind many scientific
disciplines from science to engineering. Previous studies proposed a strategy
updating mechanism, which successfully demonstrated that the scale-free network
can provide a framework for the emergence of cooperation. Instead, individuals
in random graphs and small-world networks do not favor cooperation under this
updating rule. However, a recent empirical result shows the heterogeneous
networks do not promote cooperation when humans play a Prisoner's Dilemma. In
this paper, we propose a strategy updating rule with payoff memory. We observe
that the random graphs and small-world networks can provide even better
frameworks for cooperation than the scale-free networks in this scenario. Our
observations suggest that the degree heterogeneity may be neither a sufficient
condition nor a necessary condition for the widespread cooperation in complex
networks. Also, the topological structures are not sufficed to determine the
level of cooperation in complex networks.Comment: 6 pages, 5 figure
Social dilemmas in an online social network: the structure and evolution of cooperation
We investigate two paradigms for studying the evolution of
cooperation--Prisoner's Dilemma and Snowdrift game in an online friendship
network obtained from a social networking site. We demonstrate that such social
network has small-world property and degree distribution has a power-law tail.
Besides, it has hierarchical organizations and exhibits disassortative mixing
pattern. We study the evolutionary version of the two types of games on it. It
is found that enhancement and sustainment of cooperative behaviors are
attributable to the underlying network topological organization. It is also
shown that cooperators can survive when confronted with the invasion of
defectors throughout the entire ranges of parameters of both games. The
evolution of cooperation on empirical networks is influenced by various network
effects in a combined manner, compared with that on model networks. Our results
can help understand the cooperative behaviors in human groups and society.Comment: 14 pages, 7 figure
Evolutionary game theory: Temporal and spatial effects beyond replicator dynamics
Evolutionary game dynamics is one of the most fruitful frameworks for
studying evolution in different disciplines, from Biology to Economics. Within
this context, the approach of choice for many researchers is the so-called
replicator equation, that describes mathematically the idea that those
individuals performing better have more offspring and thus their frequency in
the population grows. While very many interesting results have been obtained
with this equation in the three decades elapsed since it was first proposed, it
is important to realize the limits of its applicability. One particularly
relevant issue in this respect is that of non-mean-field effects, that may
arise from temporal fluctuations or from spatial correlations, both neglected
in the replicator equation. This review discusses these temporal and spatial
effects focusing on the non-trivial modifications they induce when compared to
the outcome of replicator dynamics. Alongside this question, the hypothesis of
linearity and its relation to the choice of the rule for strategy update is
also analyzed. The discussion is presented in terms of the emergence of
cooperation, as one of the current key problems in Biology and in other
disciplines.Comment: Review, 48 pages, 26 figure
Modeling Evolutionary Dynamics of Lurking in Social Networks
Lurking is a complex user-behavioral phenomenon that occurs in all
large-scale online communities and social networks. It generally refers to the
behavior characterizing users that benefit from the information produced by
others in the community without actively contributing back to the production of
social content. The amount and evolution of lurkers may strongly affect an
online social environment, therefore understanding the lurking dynamics and
identifying strategies to curb this trend are relevant problems. In this
regard, we introduce the Lurker Game, i.e., a model for analyzing the
transitions from a lurking to a non-lurking (i.e., active) user role, and vice
versa, in terms of evolutionary game theory. We evaluate the proposed Lurker
Game by arranging agents on complex networks and analyzing the system
evolution, seeking relations between the network topology and the final
equilibrium of the game. Results suggest that the Lurker Game is suitable to
model the lurking dynamics, showing how the adoption of rewarding mechanisms
combined with the modeling of hypothetical heterogeneity of users' interests
may lead users in an online community towards a cooperative behavior.Comment: 13 pages, 5 figures. Accepted at CompleNet 201
Leaders should not be conformists in evolutionary social dilemmas
The most common assumption in evolutionary game theory is that players should
adopt a strategy that warrants the highest payoff. However, recent studies
indicate that the spatial selection for cooperation is enhanced if an
appropriate fraction of the population chooses the most common rather than the
most profitable strategy within the interaction range. Such conformity might be
due to herding instincts or crowd behavior in humans and social animals. In a
heterogeneous population where individuals differ in their degree, collective
influence, or other traits, an unanswered question remains who should conform.
Selecting conformists randomly is the simplest choice, but it is neither a
realistic nor the optimal one. We show that, regardless of the source of
heterogeneity and game parametrization, socially the most favorable outcomes
emerge if the masses conform. On the other hand, forcing leaders to conform
significantly hinders the constructive interplay between heterogeneity and
coordination, leading to evolutionary outcomes that are worse still than if
conformists were chosen randomly. We conclude that leaders must be able to
create a following for network reciprocity to be optimally augmented by
conformity. In the opposite case, when leaders are castrated and made to
follow, the failure of coordination impairs the evolution of cooperation.Comment: 7 two-column pages, 4 figures; accepted for publication in Scientific
Reports [related work available at arXiv:1412.4113
Coevolutionary games - a mini review
Prevalence of cooperation within groups of selfish individuals is puzzling in
that it contradicts with the basic premise of natural selection. Favoring
players with higher fitness, the latter is key for understanding the challenges
faced by cooperators when competing with defectors. Evolutionary game theory
provides a competent theoretical framework for addressing the subtleties of
cooperation in such situations, which are known as social dilemmas. Recent
advances point towards the fact that the evolution of strategies alone may be
insufficient to fully exploit the benefits offered by cooperative behavior.
Indeed, while spatial structure and heterogeneity, for example, have been
recognized as potent promoters of cooperation, coevolutionary rules can extend
the potentials of such entities further, and even more importantly, lead to the
understanding of their emergence. The introduction of coevolutionary rules to
evolutionary games implies, that besides the evolution of strategies, another
property may simultaneously be subject to evolution as well. Coevolutionary
rules may affect the interaction network, the reproduction capability of
players, their reputation, mobility or age. Here we review recent works on
evolutionary games incorporating coevolutionary rules, as well as give a
didactic description of potential pitfalls and misconceptions associated with
the subject. In addition, we briefly outline directions for future research
that we feel are promising, thereby particularly focusing on dynamical effects
of coevolutionary rules on the evolution of cooperation, which are still widely
open to research and thus hold promise of exciting new discoveries.Comment: 24 two-column pages, 10 figures; accepted for publication in
BioSystem
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
Complex network analysis and nonlinear dynamics
This chapter aims at reviewing complex network and nonlinear dynamical
models and methods that were either developed for or applied to socioeconomic
issues, and pertinent to the theme of New Economic Geography. After an introduction
to the foundations of the field of complex networks, the present summary
introduces some applications of complex networks to economics, finance, epidemic
spreading of innovations, and regional trade and developments. The chapter also
reviews results involving applications of complex networks to other relevant
socioeconomic issue
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