29 research outputs found
Adoption of simultaneous different strategies against different opponents enhances cooperation
The emergence of cooperation has been widely studied in the context of game theory on structured populations. Usually the individuals adopt one strategy against all their neighbors. The structure can provide reproductive success for the cooperative strategy, at least for low values of defection tendency. Other mechanisms, such punishment, can also be responsible for cooperation emergence. But what happens if the players adopt simultaneously different strategies against each one of their opponents, not just a single one? Here we study this question in the prisoner dilemma scenario structured on a square lattice and on a ring. We show that if an update rule is defined in which the players replace the strategy that furnishes the smallest payoff, a punishment response mechanism against defectors without imputing cost to the punishers appears, cooperation dominates and, even if the tendency of defection is huge, cooperation still remains alive
Distinguishing the opponents in the prisoner dilemma in well-mixed populations
Here we study the effects of adopting different strategies against different
opponent instead of adopting the same strategy against all of them in the
prisoner dilemma structured in well-mixed populations. We consider an
evolutionary process in which strategies that provide reproductive success are
imitated and players replace one of their worst interactions by the new one. We
set individuals in a well-mixed population so that network reciprocity effect
is excluded and we analyze both synchronous and asynchronous updates. As a
consequence of the replacement rule, we show that mutual cooperation is never
destroyed and the initial fraction of mutual cooperation is a lower bound for
the level of cooperation. We show by simulation and mean-field analysis that
for synchronous update cooperation dominates while for asynchronous update only
cooperations associated to the initial mutual cooperations are maintained. As a
side effect of the replacement rule, an "implicit punishment" mechanism comes
up in a way that exploitations are always neutralized providing evolutionary
stability for cooperation
Role-separating ordering in social dilemmas controlled by topological frustration
"Three is a crowd" is an old proverb that applies as much to social
interactions, as it does to frustrated configurations in statistical physics
models. Accordingly, social relations within a triangle deserve special
attention. With this motivation, we explore the impact of topological
frustration on the evolutionary dynamics of the snowdrift game on a triangular
lattice. This topology provides an irreconcilable frustration, which prevents
anti-coordination of competing strategies that would be needed for an optimal
outcome of the game. By using different strategy updating protocols, we observe
complex spatial patterns in dependence on payoff values that are reminiscent to
a honeycomb-like organization, which helps to minimize the negative consequence
of the topological frustration. We relate the emergence of these patterns to
the microscopic dynamics of the evolutionary process, both by means of
mean-field approximations and Monte Carlo simulations. For comparison, we also
consider the same evolutionary dynamics on the square lattice, where of course
the topological frustration is absent. However, with the deletion of diagonal
links of the triangular lattice, we can gradually bridge the gap to the square
lattice. Interestingly, in this case the level of cooperation in the system is
a direct indicator of the level of topological frustration, thus providing a
method to determine frustration levels in an arbitrary interaction network.Comment: 9 two-column pages, 9 figures; accepted for publication in Physical
Review
Modern temporal network theory: A colloquium
The power of any kind of network approach lies in the ability to simplify a
complex system so that one can better understand its function as a whole.
Sometimes it is beneficial, however, to include more information than in a
simple graph of only nodes and links. Adding information about times of
interactions can make predictions and mechanistic understanding more accurate.
The drawback, however, is that there are not so many methods available, partly
because temporal networks is a relatively young field, partly because it more
difficult to develop such methods compared to for static networks. In this
colloquium, we review the methods to analyze and model temporal networks and
processes taking place on them, focusing mainly on the last three years. This
includes the spreading of infectious disease, opinions, rumors, in social
networks; information packets in computer networks; various types of signaling
in biology, and more. We also discuss future directions.Comment: Final accepted versio
The rank reversal problem in multi-criteria decision making : a literature review
Despite the importance of multicriteria decision-making (MCDM) techniques for constructing effective decision models, there are many criticisms due to the occurrence of a problem called rank reversal. Nevertheless, there is a lack of a systematic literature review on this important subject which involves different methods. This study reviews the pertinent literature on rank reversal, based on 130 related articles published from 1980 to 2015 in international journals, which were gathered and analyzed according to the following perspectives: multicriteria technique, year and journal in which the papers were published, co-authorship network, rank reversal types, and research goal. Thus our survey provides recommendations for future research, besides useful information and knowledge regarding rank reversal in the MCDM field