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Local Dynamics in Bargaining Networks via Random-Turn Games

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Internet and Network Economics (WINE 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6484))

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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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Author information

Authors and Affiliations

  1. University of Washington, USA

    L. Elisa Celis

  2. Microsoft Research, USA

    Nikhil R. Devanur & Yuval Peres

Authors
  1. L. Elisa Celis
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  2. Nikhil R. Devanur
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  3. Yuval Peres
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Editor information

Editors and Affiliations

  1. Department of Management Science and Engineering, Stanford University, 94305, Stanford, CA, USA

    Amin Saberi

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Celis, L.E., Devanur, N.R., Peres, Y. (2010). Local Dynamics in Bargaining Networks via Random-Turn Games. In: Saberi, A. (eds) Internet and Network Economics. WINE 2010. Lecture Notes in Computer Science, vol 6484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17572-5_11

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  • DOI: https://doi.org/10.1007/978-3-642-17572-5_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17571-8

  • Online ISBN: 978-3-642-17572-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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