Gradient methods for solving Stackelberg games

DOI10.1007/978-3-030-31489-7_9zbMath1431.91072arXiv1908.06901OpenAlexW2979998532MaRDI QIDQ2290375

Roi Naveiro, David Ríos Insua

Publication date: 27 January 2020

Full work available at URL: https://arxiv.org/abs/1908.06901

zbMATH Keywords

game theoryautomatic differentiationadjoint methodadversarial machine learning

Mathematics Subject Classification ID

Hierarchical games (including Stackelberg games) (91A65) Algorithmic game theory and complexity (91A68)

Related Items

Adversarial Machine Learning: Bayesian Perspectives ⋮ Augmented probability simulation methods for sequential games

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