IDEAS home Printed from
   My bibliography  Save this article

Learning to Coordinate in Social Networks


  • Pooya Molavi

    () (Department of Economics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

  • Ceyhun Eksin

    () (School of Electrical and Computer Engineering and School of Biology, Georgia Inst. of Technology, Atlanta, Georgia 30332)

  • Alejandro Ribeiro

    () (Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Ali Jadbabaie

    () (Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104)


We study a dynamic game in which short-run players repeatedly play a symmetric, strictly supermodular game whose payoffs depend on a fixed unknown state of nature. Each short-run player inherits the beliefs of his immediate predecessor in addition to observing the actions of the players in his social neighborhood in the previous stage. Because of the strategic complementary between their actions, players have the incentive to coordinate with others and learn from them. We show that in any Markov Bayesian equilibrium of the game, players eventually reach consensus in their actions. They also asymptotically receive similar payoffs despite initial differences in their access to information. We further show that, if the players’ payoffs can be represented by a quadratic function, then the private observations are optimally aggregated in the limit for generic specifications of the game. Therefore, players asymptotically coordinate on choosing the best action given the aggregate information available throughout the network. We provide extensions of our results to the case of changing networks and endogenous private signals.

Suggested Citation

  • Pooya Molavi & Ceyhun Eksin & Alejandro Ribeiro & Ali Jadbabaie, 2016. "Learning to Coordinate in Social Networks," Operations Research, INFORMS, vol. 64(3), pages 605-621, June.
  • Handle: RePEc:inm:oropre:v:64:y:2016:i:3:p:605-621

    Download full text from publisher

    File URL:
    Download Restriction: no


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:oropre:v:64:y:2016:i:3:p:605-621. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.