26,116 research outputs found
Stationary Mean Field Games systems defined on networks
We consider a stationary Mean Field Games system defined on a network. In
this framework, the transition conditions at the vertices play a crucial role:
the ones here considered are based on the optimal control interpretation of the
problem. We prove separately the well-posedness for each of the two equations
composing the system. Finally, we prove existence and uniqueness of the
solution of the Mean Field Games system
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
Stochastic Differential Games and Energy-Efficient Power Control
One of the contributions of this work is to formulate the problem of
energy-efficient power control in multiple access channels (namely, channels
which comprise several transmitters and one receiver) as a stochastic
differential game. The players are the transmitters who adapt their power level
to the quality of their time-varying link with the receiver, their battery
level, and the strategy updates of the others. The proposed model not only
allows one to take into account long-term strategic interactions but also
long-term energy constraints. A simple sufficient condition for the existence
of a Nash equilibrium in this game is provided and shown to be verified in a
typical scenario. As the uniqueness and determination of equilibria are
difficult issues in general, especially when the number of players goes large,
we move to two special cases: the single player case which gives us some useful
insights of practical interest and allows one to make connections with the case
of large number of players. The latter case is treated with a mean-field game
approach for which reasonable sufficient conditions for convergence and
uniqueness are provided. Remarkably, this recent approach for large system
analysis shows how scalability can be dealt with in large games and only relies
on the individual state information assumption.Comment: The final publication is available at
http://www.springerlink.com/openurl.asp?genre=article\&id=doi:10.1007/s13235-012-0068-
A numerical method for Mean Field Games on networks
We propose a numerical method for stationary Mean Field Games defined on a
network. In this framework a correct approximation of the transition conditions
at the vertices plays a crucial role. We prove existence, uniqueness and
convergence of the scheme and we also propose a least squares method for the
solution of the discrete system. Numerical experiments are carried out
Mean field game model of corruption
A simple model of corruption that takes into account the effect of the
interaction of a large number of agents by both rational decision making and
myopic behavior is developed. Its stationary version turns out to be a rare
example of an exactly solvable model of mean-field-game type. The results show
clearly how the presence of interaction (including social norms) influences the
spread of corruption
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