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Convergence to equilibrium in local interaction games

Convergence to equilibrium in local interaction games We study a simple game-theoretic model for the spread of an innovation in a network. The diffiusion 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGecom Exchanges Association for Computing Machinery

Convergence to equilibrium in local interaction games

Montanari, Andrea; Saberi, Amin
ACM SIGecom Exchanges , Volume 8 (1) – Jul 1, 2009
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Publisher
Association for Computing Machinery
Copyright
The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc.
Subject
Modeling methodologies
ISSN
1551-9031
DOI
10.1145/1598780.1598791
Publisher site
See Article on Publisher Site

Abstract

We study a simple game-theoretic model for the spread of an innovation in a network. The diffiusion 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.

Journal

ACM SIGecom Exchanges – Association for Computing Machinery

Published: Jul 1, 2009

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