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Learning with whom to Interact: A Public Good Game on a Dynamic Network

Greiff, Matthias
2013
  • Controlled Vocabulary...

Abstract
We use a public good game with rewards, played on a dynamic network, to illustrate how self-organizing communities can achieve the provision of a public good without a central authority or privatization. Given that rewards are given to contributors and that the choice of whom to reward depends on social distance, free-riders will be excluded from rewards and the (almost efficient) provision of a public good becomes possible. We review the related experimental economics literature and illustrate how the model can be tested in the laboratory.
Archivio
http://hdl.handle.net/10077/9677
Diritti
open access
Soggetti
  • Dynamic networks

  • evolutionary game the...

  • public goods

  • reinforcement learnin...

  • social networks

Visualizzazioni
4
Data di acquisizione
Apr 19, 2024
Vedi dettagli
google-scholar
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