2,401 research outputs found
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
Evolutionary Multiplayer Games
Evolutionary game theory has become one of the most diverse and far reaching
theories in biology. Applications of this theory range from cell dynamics to
social evolution. However, many applications make it clear that inherent
non-linearities of natural systems need to be taken into account. One way of
introducing such non-linearities into evolutionary games is by the inclusion of
multiple players. An example is of social dilemmas, where group benefits could
e.g.\ increase less than linear with the number of cooperators. Such
multiplayer games can be introduced in all the fields where evolutionary game
theory is already well established. However, the inclusion of non-linearities
can help to advance the analysis of systems which are known to be complex, e.g.
in the case of non-Mendelian inheritance. We review the diachronic theory and
applications of multiplayer evolutionary games and present the current state of
the field. Our aim is a summary of the theoretical results from well-mixed
populations in infinite as well as finite populations. We also discuss examples
from three fields where the theory has been successfully applied, ecology,
social sciences and population genetics. In closing, we probe certain future
directions which can be explored using the complexity of multiplayer games
while preserving the promise of simplicity of evolutionary games.Comment: 14 pages, 2 figures, review pape
Mean-field-game model for Botnet defense in Cyber-security
We initiate the analysis of the response of computer owners to various offers
of defence systems
against a cyber-hacker (for instance, a botnet attack), as a stochastic game
of a large number of interacting agents. We introduce a simple mean-field game
that models their behavior. It takes into account both the random process of
the propagation of the infection (controlled by the botner herder) and the
decision making process of customers. Its stationary version turns out to be
exactly solvable (but not at all trivial) under an additional natural
assumption that the execution time of the decisions of the customers (say,
switch on or out the defence system) is much faster that the infection rates
- …