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Deterministic approximation of stochastic evolution in games

Auteur(s)
Benaim, Michel 
Institut de mathématiques 
Weibull, Jorgen W
Date de parution
2003
In
Econometrica
Vol.
3
No
71
De la page
873
A la page
903
Mots-clés
  • game theory
  • evolution
  • approximation
  • large deviations
  • Markov chains
  • DYNAMICAL-SYSTEMS
  • STABLE STRATEGIES
  • MIXED EQUILIBRIA
  • SELECTION
  • ALGORITHMS
  • STABILITY
  • PLAY
  • game theory

  • evolution

  • approximation

  • large deviations

  • Markov chains

  • DYNAMICAL-SYSTEMS

  • STABLE STRATEGIES

  • MIXED EQUILIBRIA

  • SELECTION

  • ALGORITHMS

  • STABILITY

  • PLAY

Résumé
This paper provides deterministic approximation results for stochastic processes that arise when finite populations recurrently play finite games. The processes are Markov chains, and the approximation is defined in continuous time as a system of ordinary differential equations of the type studied in evolutionary game theory. We establish precise connections between the long-run behavior of the discrete stochastic process, for large populations, and its deterministic flow approximation. In particular, we provide probabilistic bounds on exit times from and visitation rates to neighborhoods of attractors; to the deterministic flow. We sharpen these results in the special case of ergodic processes.
Identifiants
https://libra.unine.ch/handle/123456789/6276
Type de publication
journal article
Dossier(s) à télécharger
 main article: Econometrica - 2003 - Benaïm - Deterministic Approximation of Stochastic Evolution in Games.pdf (221.71 KB)
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