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- W2060821413 abstract "We consider optimal selection problems, where the number N 1 of candidates for the job is random, and the times of arrival of the candidates are uniformly distributed in [0, 1]. Such best choice problems are generally harder than the fixed- N counterparts, because there is a learning process going on as one observes the times of arrivals, giving information about the likely values of N 1 . In certain special cases, notably when N 1 is geometrically distributed, it had been proved earlier that the optimal policy was of a very simple form; this paper will explain why these cases are so simple by embedding the process in a planar Poisson process from which all the requisite distributional results can be read off by inspection. Routine stochastic calculus methods are then used to prove the conjectured optimal policy." @default.
- W2060821413 created "2016-06-24" @default.
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- W2060821413 date "1991-08-01" @default.
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- W2060821413 title "Embedding optimal selection problems in a Poisson process" @default.
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- W2060821413 doi "https://doi.org/10.1016/0304-4149(91)90094-s" @default.
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