2 research outputs found
Statistical mechanics of spatial evolutionary games
We discuss the long-run behavior of stochastic dynamics of many interacting
players in spatial evolutionary games. In particular, we investigate the effect
of the number of players and the noise level on the stochastic stability of
Nash equilibria. We discuss similarities and differences between systems of
interacting players maximizing their individual payoffs and particles
minimizing their interaction energy. We use concepts and techniques of
statistical mechanics to study game-theoretic models. In order to obtain
results in the case of the so-called potential games, we analyze the
thermodynamic limit of the appropriate models of interacting particles.Comment: 19 pages, to appear in J. Phys.
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