Abstract

We prove that differential Nash equilibria are generic amongst local Nash equilibria in continuous zerosum games. That is, there exists an open-dense subset of zero-sum games for which local Nash equilibria are nondegenerate differential Nash equilibria. The result extends previous results to the zero-sum setting, where we obtain even stronger results; in particular, we show that local Nash equilibria are generically hyperbolic critical points. We further show that differential Nash equilibria of zero-sum games are structurally stable. The purpose for presenting these extensions is the recent renewed interest in zero-sum games within machine learning and optimization. Adversarial learning and generative adversarial network approaches are touted to be more robust than the alternative. Zero-sum games are at the heart of such approaches. Many works proceed under the assumption of hyperbolicity of critical points. Our results justify this assumption by showing ‘almost all’ zero-sum games admit local Nash equilibria that are hyperbolic.

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