19,277 research outputs found
Metric clusters in evolutionary games on scale-free networks
The evolution of cooperation in social dilemmas in structured populations has
been studied extensively in recent years. Whereas many theoretical studies have
found that a heterogeneous network of contacts favors cooperation, the impact
of spatial effects in scale-free networks is still not well understood. In
addition to being heterogeneous, real contact networks exhibit a high mean
local clustering coefficient, which implies the existence of an underlying
metric space. Here, we show that evolutionary dynamics in scale-free networks
self-organize into spatial patterns in the underlying metric space. The
resulting metric clusters of cooperators are able to survive in social dilemmas
as their spatial organization shields them from surrounding defectors, similar
to spatial selection in Euclidean space. We show that under certain conditions
these metric clusters are more efficient than the most connected nodes at
sustaining cooperation and that heterogeneity does not always favor--but can
even hinder--cooperation in social dilemmas. Our findings provide a new
perspective to understand the emergence of cooperation in evolutionary games in
realistic structured populations
Dynamic Learning, Herding and Guru Effects in Networks
It has been widely accepted that herding is the consequence of mimetic responses by agents interacting locally on a communication network. In extant models, this communication network linking agents, by and large, has been assumed to be fixed. In this paper we allow it to evolve endogenously by enabling agents to adaptively modify the weights of their links to their neighbours by reinforcing �good� advisors and breaking away from �bad� advisors with the latter being replaced randomly from the remaining agents. The resulting network not only allows for herding of agents, but crucially exhibits realistic properties of socio-economic networks that are otherwise difficult to replicate: high clustering, short average path length and a small number of highly connected agents, called "gurus". These properties are now well understood to characterize �small world networks� of Watts and Strogatz (1998).
Multirelational Organization of Large-scale Social Networks in an Online World
The capacity to collect fingerprints of individuals in online media has
revolutionized the way researchers explore human society. Social systems can be
seen as a non-linear superposition of a multitude of complex social networks,
where nodes represent individuals and links capture a variety of different
social relations. Much emphasis has been put on the network topology of social
interactions, however, the multi-dimensional nature of these interactions has
largely been ignored in empirical studies, mostly because of lack of data.
Here, for the first time, we analyze a complete, multi-relational, large social
network of a society consisting of the 300,000 odd players of a massive
multiplayer online game. We extract networks of six different types of
one-to-one interactions between the players. Three of them carry a positive
connotation (friendship, communication, trade), three a negative (enmity, armed
aggression, punishment). We first analyze these types of networks as separate
entities and find that negative interactions differ from positive interactions
by their lower reciprocity, weaker clustering and fatter-tail degree
distribution. We then proceed to explore how the inter-dependence of different
network types determines the organization of the social system. In particular
we study correlations and overlap between different types of links and
demonstrate the tendency of individuals to play different roles in different
networks. As a demonstration of the power of the approach we present the first
empirical large-scale verification of the long-standing structural balance
theory, by focusing on the specific multiplex network of friendship and enmity
relations.Comment: 7 pages, 5 figures, accepted for publication in PNA
Evolutionary games on multilayer networks: A colloquium
Networks form the backbone of many complex systems, ranging from the Internet
to human societies. Accordingly, not only is the range of our interactions
limited and thus best described and modeled by networks, it is also a fact that
the networks that are an integral part of such models are often interdependent
or even interconnected. Networks of networks or multilayer networks are
therefore a more apt description of social systems. This colloquium is devoted
to evolutionary games on multilayer networks, and in particular to the
evolution of cooperation as one of the main pillars of modern human societies.
We first give an overview of the most significant conceptual differences
between single-layer and multilayer networks, and we provide basic definitions
and a classification of the most commonly used terms. Subsequently, we review
fascinating and counterintuitive evolutionary outcomes that emerge due to
different types of interdependencies between otherwise independent populations.
The focus is on coupling through the utilities of players, through the flow of
information, as well as through the popularity of different strategies on
different network layers. The colloquium highlights the importance of pattern
formation and collective behavior for the promotion of cooperation under
adverse conditions, as well as the synergies between network science and
evolutionary game theory.Comment: 14 two-column pages, 8 figures; accepted for publication in European
Physical Journal
Mutual Trust and Cooperation in the Evolutionary Hawks-Doves Game
Using a new dynamical network model of society in which pairwise interactions
are weighted according to mutual satisfaction, we show that cooperation is the
norm in the Hawks-Doves game when individuals are allowed to break ties with
undesirable neighbors and to make new acquaintances in their extended
neighborhood. Moreover, cooperation is robust with respect to rather strong
strategy perturbations. We also discuss the empirical structure of the emerging
networks, and the reasons that allow cooperators to thrive in the population.
Given the metaphorical importance of this game for social interaction, this is
an encouraging positive result as standard theory for large mixing populations
prescribes that a certain fraction of defectors must always exist at
equilibrium.Comment: 23 pages 12 images, to appea
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