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In this paper, we study three asymptotic regimes that can be applied toranking and selection (R&S) problems with general sample distributions. Theseasymptotic regimes are constructed by sending particular problem parameters(probability of incorrect selection, smallest difference in system performancethat we deem worth detecting) to zero. We establish asymptotic validity andefficiency of the corresponding R&S procedures in each regime. We also analyzethe connection among different regimes and compare the pre-limit performancesof corresponding algorithms.

Three Asymptotic Regimes for Ranking and Selection with General Sample Distributions