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This paper is devoted to the study of the max K-armed bandit problem, whichconsists in sequentially allocating resources in order to detect extremevalues. Our contribution is twofold. We first significantly refine the analysisof the ExtremeHunter algorithm carried out in Carpentier and Valko (2014), andnext propose an alternative approach, showing that, remarkably, Extreme Banditscan be reduced to a classical version of the bandit problem to a certainextent. Beyond the formal analysis, these two approaches are compared throughnumerical experiments.

Max K-armed bandit: On the ExtremeHunter algorithm and beyond