Neural networks and contagion
Bibliographic Data
| ID | 19173145 |
|---|---|
| Authors | Siegfried K Berninghaus (corresponding author), Siegfried Berninghaus (Institut de théorie économique et de recherche opérationnelle à l’Université de Karlsruhe (Institut für Wirtschaftstheorie und Operations Research (WIOR))), Hans Haller (0000-0001-9957-7499, Virginia Polytechnic Institute and State University, Blacksburg (USA)), Alexander V Outkin (0000-0001-6922-8343, Los Alamos National Laboratory), Alexander Outkin (Decision Applications Division, Los Alamos National Laboratory (USA)) |
| Year | 2006 |
| Volume | 114-115 |
| Pages | 205-224 |
| Publication date | 2006-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Revue d économie industrielle (JOURNAL) |
| Journal identifiers | ISSN: 0154-3229 • E-ISSN: 1773-0198 |
| Publisher | Éditions De Boeck Supérieur (PUBLISHER) |
| DOI | 10.4000/rei.403 |
| OpenAlex | W2009932644 |
| Language | EN |
| References cited | 6 |
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
Artificial neural network · Econometrics · Logistic function · Logistic regression · Logit · Mathematical analysis · Maxima and minima · Physics · Population · Sociology · Statistical physics · Statistics · Computer Science · Demography · Game Theory and Applications · Mathematical Biology Tumor Growth · Mathematics · Opinion Dynamics and Social Influence · Artificial Intelligence
| Highly cited | No |
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