Learning in anonymous nonatomic games with applications to first-order mean field games

Saeed Hadikhanloo

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arXiv · 1704.00378

Learning in anonymous nonatomic games with applications to first-order mean field games

Saeed Hadikhanloo

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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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Saeed Hadikhanloo. 2017-04-02. Learning in anonymous nonatomic games with applications to first-order mean field games. https://arxiv.org/abs/1704.00378

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