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Neural networks and contagion

Author

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  • Siegfried Berninghaus
  • Hans Haller
  • Alexander Outkin

Abstract

Nous analysons les phénomènes de contagion apparaissant dans des situtions d?interaction locale ou globale. Nous utilisons les réseaux de neurones pour étudier ces phénomènes. Contrairement à beaucoup de modèles, un état de système décrit la structure spatiale des choix et non pas uniquement la fréquence avec laquelle chaque action est jouée dans la population. Les dynamiques de réponses optimales bruitée à l?aide d?une loi logistique génèrent un modèle de décision logit. La distribution stationnaire du processus est de type Gibbs-Boltzann. Les équilibres de long terme sont les états qui maximisent une fonction de potentiel.

Suggested Citation

  • Siegfried Berninghaus & Hans Haller & Alexander Outkin, 2006. "Neural networks and contagion," Revue d'économie industrielle, De Boeck Université, vol. 0(2), pages 11-11.
    • Handle: RePEc:cai:reidbu:rei_114_0011
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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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