Learning in games using the imprecise Dirichlet model

• Autores: Erik Quaeghebeur, Gert de Cooman
• Localización: International journal of approximate reasoning, ISSN 0888-613X, Vol. 50, Nº 2, 2009, págs. 243-256
• Idioma: inglés
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• Resumen

  • We propose a new learning model for finite strategic-form two-player games based on fictitious play and Walley�s imprecise Dirichlet model [P. Walley, Inferences from multinomial data: learning about a bag of marbles, J. Roy. Statist. Soc. B 58 (1996) 3�57]. This model allows the initial beliefs of the players about their opponent�s strategy choice to be near-vacuous or imprecise instead of being precisely defined. A similar generalization can be made as the one proposed by Fudenberg and Kreps [D. Fudenberg, D.M. Kreps, Learning mixed equilibria, Games Econ. Behav. 5 (1993) 320�367] for fictitious play, where assumptions about immediate behavior are replaced with assumptions about asymptotic behavior. We also obtain similar convergence results for this generalization: if there is convergence, it will be to an equilibrium.