In this paper, we introduce an over-time variant of the well-known prophet-inequality with i.i.d. random variables. Instead of stopping with one realized value at some point in the process, we decide for each step how long we select the value. Then we cannot select another value until this period is over. The goal is to maximize the expectation of the sum of selected values. We describe the structure of the optimal stopping rule and give upper and lower bounds on the prophet-inequality. - Which, in online algorithms terminology, corresponds to bounds on the competitive ratio of an online algorithm. We give a surprisingly simple algorithm with a single threshold that results in a prophet-inequality of $\approx 0.396$ for all input lengths $n$. Additionally, as our main result, we present a more advanced algorithm resulting in a prophet-inequality of $\approx 0.598$ when the number of steps tends to infinity. We complement our results by an upper bound that shows that the best possible prophet-inequality is at most $1/\varphi \approx 0.618$, where $\varphi$ denotes the golden ratio. As part of the proof, we give an advanced bound on the weighted mediant.
翻译:在本文中,我们引入了已知先知与i.d.随机变量不平等的超时变式。 我们不是在过程的某一点用一个已实现的值停下来,而是为每个步骤选择一个已实现的值,而是为每个步骤决定我们选择该值的长度。 然后我们无法在这个时期结束之前选择另一个值。 目标是尽量扩大选定值之和的预期值。 我们描述最佳停止规则的结构, 并给先知与不平等的上限和下限。 在在线算法术语中, 与在线算法的竞争比率的界限相对应。 我们给出了一个惊人的简单算法, 其单一的门槛导致所有输入长度的预知- 0. 396美元 。 此外, 作为我们的主要结果, 我们提出了一个更先进的算法, 当步骤数量趋向于无限的时候, 0. 598美元 。 我们用一个上限来补充我们的结果, 它显示, 最可能的预言-不均匀值最多为 $/\ varphie\ approx 0.618美元, 其中, 美元是黄金的加权比例。