21,687 research outputs found
Evolutionary games on graphs
Game theory is one of the key paradigms behind many scientific disciplines
from biology to behavioral sciences to economics. In its evolutionary form and
especially when the interacting agents are linked in a specific social network
the underlying solution concepts and methods are very similar to those applied
in non-equilibrium statistical physics. This review gives a tutorial-type
overview of the field for physicists. The first three sections introduce the
necessary background in classical and evolutionary game theory from the basic
definitions to the most important results. The fourth section surveys the
topological complications implied by non-mean-field-type social network
structures in general. The last three sections discuss in detail the dynamic
behavior of three prominent classes of models: the Prisoner's Dilemma, the
Rock-Scissors-Paper game, and Competing Associations. The major theme of the
review is in what sense and how the graph structure of interactions can modify
and enrich the picture of long term behavioral patterns emerging in
evolutionary games.Comment: Review, final version, 133 pages, 65 figure
Topological enslavement in evolutionary games on correlated multiplex networks
Governments and enterprises strongly rely on incentives to generate favorable
outcomes from social and strategic interactions between individuals. The
incentives are usually modeled by payoffs in evolutionary games, such as the
prisoner's dilemma or the harmony game, with imitation dynamics. Adjusting the
incentives by changing the payoff parameters can favor cooperation, as found in
the harmony game, over defection, which prevails in the prisoner's dilemma.
Here, we show that this is not always the case if individuals engage in
strategic interactions in multiple domains. In particular, we investigate
evolutionary games on multiplex networks where individuals obtain an aggregate
payoff. We explicitly control the strength of degree correlations between nodes
in the different layers of the multiplex. We find that if the multiplex is
composed of many layers and degree correlations are strong, the topology of the
system enslaves the dynamics and the final outcome, cooperation or defection,
becomes independent of the payoff parameters. The fate of the system is then
determined by the initial conditions
Evolutionary Prisoner's Dilemma on heterogeneous Newman-Watts small-world network
We focus on the heterogeneity of social networks and its role to the
emergence of prevailing cooperation and sustaining cooperators. The social
networks are representative of the interaction relationships between players
and their encounters in each round of games. We study an evolutionary
Prisoner's Dilemma game on a variant of Watts-Strogatz small-world network,
whose heterogeneity can be tuned by a parameter. It is found that optimal
cooperation level exists at some intermediate topological heterogeneity for
different temptations to defect. Moreover, neither the most heterogeneous case
nor the most homogeneous one would favor the cooperators. At intermediate
heterogeneity in degree sequences, cooperators could resist the invasion of
defectors for large temptation to defect.Comment: Updated versio
Conformity enhances network reciprocity in evolutionary social dilemmas
The pursuit of highest payoffs in evolutionary social dilemmas is risky and
sometimes inferior to conformity. Choosing the most common strategy within the
interaction range is safer because it ensures that the payoff of an individual
will not be much lower than average. Herding instincts and crowd behavior in
humans and social animals also compel to conformity on their own right.
Motivated by these facts, we here study the impact of conformity on the
evolution of cooperation in social dilemmas. We show that an appropriate
fraction of conformists within the population introduces an effective surface
tension around cooperative clusters and ensures smooth interfaces between
different strategy domains. Payoff-driven players brake the symmetry in favor
of cooperation and enable an expansion of clusters past the boundaries imposed
by traditional network reciprocity. This mechanism works even under the most
testing conditions, and it is robust against variations of the interaction
network as long as degree-normalized payoffs are applied. Conformity may thus
be beneficial for the resolution of social dilemmas.Comment: 8 two-column pages, 5 figures; accepted for publication in Journal of
the Royal Society Interfac
Cooperation with both synergistic and local interactions can be worse than each alone
Cooperation is ubiquitous ranging from multicellular organisms to human
societies. Population structures indicating individuals' limited interaction
ranges are crucial to understand this issue. But it is still at large to what
extend multiple interactions involving nonlinearity in payoff play a role on
cooperation in structured populations. Here we show a rule, which determines
the emergence and stabilization of cooperation, under multiple discounted,
linear, and synergistic interactions. The rule is validated by simulations in
homogenous and heterogenous structured populations. We find that the more
neighbors there are the harder for cooperation to evolve for multiple
interactions with linearity and discounting. For synergistic scenario, however,
distinct from its pairwise counterpart, moderate number of neighbors can be the
worst, indicating that synergistic interactions work with strangers but not
with neighbors. Our results suggest that the combination of different factors
which promotes cooperation alone can be worse than that with every single
factor.Comment: 32 pages, 4 figure
Public Goods in Networks with Constraints on Sharing
This paper considers incentives to provide goods that are partially
excludable along social links. We introduce a model in which each individual in
a networked society makes a two-pronged decision: (i) decide how much of the
good to provide, and (ii) decide which subset of neighbours to nominate as
co-beneficiaries. An outcome specifies an endogenous subnetwork generated by
nominations and a public goods game occurring over the realised subnetwork. We
show the existence of specialised pure strategy Nash equilibria: those in which
some individuals (the Drivers) contribute while the remaining individuals (the
Passengers) free ride. We then consider how the set of efficient specialised
equilibria vary as the constraints on sharing are relaxed and we show a
monotonicity result. Finally, we introduce dynamics and show that only
specialised equilibria can be stable against individuals unilaterally changing
their provision level
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
Threshold games and cooperation on multiplayer graphs
Objective: The study investigates the effect on cooperation in multiplayer
games, when the population from which all individuals are drawn is structured -
i.e. when a given individual is only competing with a small subset of the
entire population.
Method: To optimize the focus on multiplayer effects, a class of games were
chosen for which the payoff depends nonlinearly on the number of cooperators -
this ensures that the game cannot be represented as a sum of pair-wise
interactions, and increases the likelihood of observing behaviour different
from that seen in two-player games. The chosen class of games are named
"threshold games", and are defined by a threshold, , which describes the
minimal number of cooperators in a given match required for all the
participants to receive a benefit. The model was studied primarily through
numerical simulations of large populations of individuals, each with
interaction neighbourhoods described by various classes of networks.
Results: When comparing the level of cooperation in a structured population
to the mean-field model, we find that most types of structure lead to a
decrease in cooperation. This is both interesting and novel, simply due to the
generality and breadth of relevance of the model - it is likely that any model
with similar payoff structure exhibits related behaviour.
More importantly, we find that the details of the behaviour depends to a
large extent on the size of the immediate neighbourhoods of the individuals, as
dictated by the network structure. In effect, the players behave as if they are
part of a much smaller, fully mixed, population, which we suggest an expression
for.Comment: in PLOS ONE, 4th Feb 201
Evolutionary multiplayer games on graphs with edge diversity
Evolutionary game dynamics in structured populations has been extensively
explored in past decades. However, most previous studies assume that payoffs of
individuals are fully determined by the strategic behaviors of interacting
parties and social ties between them only serve as the indicator of the
existence of interactions. This assumption neglects important information
carried by inter-personal social ties such as genetic similarity, geographic
proximity, and social closeness, which may crucially affect the outcome of
interactions. To model these situations, we present a framework of evolutionary
multiplayer games on graphs with edge diversity, where different types of edges
describe diverse social ties. Strategic behaviors together with social ties
determine the resulting payoffs of interactants. Under weak selection, we
provide a general formula to predict the success of one behavior over the
other. We apply this formula to various examples which cannot be dealt with
using previous models, including the division of labor and relationship- or
edge-dependent games. We find that labor division facilitates collective
cooperation by decomposing a many-player game into several games of smaller
sizes. The evolutionary process based on relationship-dependent games can be
approximated by interactions under a transformed and unified game. Our work
stresses the importance of social ties and provides effective methods to reduce
the calculating complexity in analyzing the evolution of realistic systems.Comment: 50 pages, 7 figure
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