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Learning in anonymous nonatomic games with applications to first-order mean field games
Published 2 Apr 2017 in math.OC | (1704.00378v1)
Abstract: We introduce a model of anonymous games with the player dependent action sets. We propose several learning procedures based on the well-known Fictitious Play and Online Mirror Descent and prove their convergence to equilibrium under the classical monotonicity condition. Typical examples are first-order mean field games.
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