Local Dynamics in Bargaining Networks via Random-Turn Games

  • L. Elisa Celis
  • Nikhil R. Devanur
  • Yuval Peres
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6484)

Abstract

We present a new technique for analyzing the rate of convergence of local dynamics in bargaining networks. The technique reduces balancing in a bargaining network to optimal play in a random-turn game. We analyze this game using techniques from martingale and Markov chain theory. We obtain a tight polynomial bound on the rate of convergence for a nontrivial class of unweighted graphs (the previous known bound was exponential). Additionally, we show this technique extends naturally to many other graphs and dynamics.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • L. Elisa Celis
    • 1
  • Nikhil R. Devanur
    • 2
  • Yuval Peres
    • 2
  1. 1.University of Washington 
  2. 2.Microsoft Research 

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