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Neural Networks and Contagion

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  • Berninghaus, Siegfried
  • Haller, Hans
  • Outkin, Alexander

Abstract

We analyze local as well as global interaction and contagion in population games, using the formalism of neural networks. In contrast to much of the literature, a state encodes not only the frequency of play, but also the spatial pattern of play. Stochastic best response dynamics with logistic noise gives rise to a log-linear or logit response model. The stationary distribution is of the Gibbs-Boltzmann type. The long-run equilibria are the maxima of a potential function.

Suggested Citation

  • Berninghaus, Siegfried & Haller, Hans & Outkin, Alexander, 2005. "Neural Networks and Contagion," Papers 05-35, Sonderforschungsbreich 504.
    • Handle: RePEc:mnh:spaper:2626
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    Cited by:

    1. Jacques Durieu & Philippe Solal, 2012. "Models of Adaptive Learning in Game Theory," Chapters, in: Richard Arena & Agnès Festré & Nathalie Lazaric (ed.), Handbook of Knowledge and Economics, chapter 11, Edward Elgar Publishing.
    2. Berninghaus, Siegfried & Haller, Hans, 2007. "Pairwise interaction on random graphs," Papers 06-16, Sonderforschungsbreich 504.

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