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Learning to Play Approximate Nash Equilibria in Games with Many Players Author info | Abstract | Publisher info | Download info | Related research | Statistics Edward Cartwright (Department of Economics, University of Warwick)
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We illustrate one way in which a population of boundedly rational individuals can learn to play an approximate Nash equilibrium. Players are assumed to make strategy choices using a combination of imitation and innovation. We begin by looking at an imitation dynamic and provide conditions under which play evolves to an imitation equilibrium; convergence is conditional on the network of social interaction. We then illustrate, through example, how imitation and innovation can complement each other; in particular, we demonstrate how imitation can .help. a population to learn to play a Nash equilibrium where more rational methods do not. This leads to our main result in which we provide a general class of large game for which the imitation with innovation dynamic almost surely converges to an approximate Nash, imitation equilibrium.
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Paper provided by Fondazione Eni Enrico Mattei in its series Working Papers with number
2004.85.
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Date of creation: May 2004Date of revision:
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Keywords: Imitation ; Best replay ; Convergence ; Nash equilibrium ; Other versions of this item:
Find related papers by JEL classification: C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
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references Cited by : (explanations , Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.)
Edward Cartwright, 2004.
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Edward Cartwright & Myrna Wooders, 2005.
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