We study a simple game-theoretic model for the spread of an innovation in a network. The diffusion of the innovation is modeled as the dynamics of a coordination game in which the adoption of a common strategy between players has a higher payoff. Classical results in game theory provide a simple condition for the innovation to spread through the network. The present paper characterizes the rate of convergence as a function of graph structure. In particular, we derive a dichotomy between well-connected (e.g. random) graphs that show slow convergence and poorly connected, low dimensional graphs that show fast convergence.
For instance, Montanari and Saberi REF attend to a game theoretic model for the diffusion of an innovation in a network and characterize the rate of convergence as a function of graph structure.
Convergence to equilibrium in local interaction games
SECO
Computer Science Mathematics