An additive allocation procedure for distributionally robust ranking and selection is proven consistent, with only k+m-1 scenarios sampled infinitely often as the budget grows.
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Additive Distributionally Robust Ranking and Selection
An additive allocation procedure for distributionally robust ranking and selection is proven consistent, with only k+m-1 scenarios sampled infinitely often as the budget grows.