Convergence to Equilibrium in Local Interaction Games

— 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 an innovation to become widespread in 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.

• Type: Conference
• Year: 2009
• Where: FOCS
• Authors: Andrea Montanari, Amin Saberi
• Keywords: FOCS 2009, Game Theoretic Model, Innovation, Low Dimensional Graphs, Theoretical Computer Science