Sharp Inequalities for Optimal Stopping with Rewards Based on RanksThe Annals of Applied Probability
AbstractA universal bound for the maximal expected reward is obtained for stopping a sequence of independent random variables where the reward is a nonincreasing function of the rank of the variable selected. This bound is shown to be sharp in three classical cases: (i) when maximizing the probability of choosing one of the k best; (ii) when minimizing the expected rank; and (iii) for an exponential function of the rank.
Citation InformationTheodore P. Hill and D. P. Kennedy. "Sharp Inequalities for Optimal Stopping with Rewards Based on Ranks" The Annals of Applied Probability Vol. 2 Iss. 2 (1992) p. 503 - 517
Available at: http://works.bepress.com/tphill/50/