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Lecture Notes in Computer Science
We introduce a class of "stochastic covering" problems where the target set X to be covered is fixed, while the "items" used in the covering are characterized by probability distributions over subsets of X. This is a natural counterpart to the stochastic packing problems introduced in  . In analogy to , we study both adaptive and non-adaptive strategies to find a feasible solution, and in particular the adaptivity gap, introduced in . It turns out that in contrast to deterministicdoi:10.1007/11682462_50 fatcat:gkymtysxzfdaniy53yl7hetcva