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No-Regret Learning in Stackelberg Security Games with an Unknown, Bounded Set of Attacker Types
In a repeated Stackelberg security game, a defender commits in every round to a randomized allocation of its resources, and an attacker, drawn from a set of types, best-responds. Existing no-regret guarantees assume that the defender knows this set of types in advance. We drop this assumption: the s
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