We consider the prophet inequality problem for (not necessarily bipartite) matching problems with independent edge values, under both edge arrivals and vertex arrivals. We show constant-factor prophet inequalities for the case where the online algorithm has only limited access to the value distributions through samples. First, we give a $16$-approximate prophet inequality for matching in general graphs under edge arrivals that uses only a single sample from each value distribution as prior information. Then, for bipartite matching and (one-sided) vertex arrivals, we show an improved bound of $8$ that also uses just a single sample from each distribution. Finally, we show how to turn our $16$-approximate single-sample prophet inequality into a truthful single-sample mechanism for online bipartite matching with vertex arrivals.
翻译:我们考虑先知的不平等问题(不一定是双面的),在边缘抵达和顶端抵达下,先知的不平等问题都与独立的边缘值问题相对应。我们展示了持续因素先知的不平等,因为在线算法只能有限地通过样本获得价值分布。首先,我们给出了大约1,600美元的预言不平等,用于在边缘抵达下对一般图表进行匹配,而边缘抵达只使用每个价值分布的单一样本作为先前的信息。然后,对于双面匹配和(片面的)顶端抵达者,我们展示了8美元的改进范围,也只使用每批发的单一样本。最后,我们展示了如何将我们大约1,600美元的单面先知不平等转化为一个真实的单一抽样机制,用于网上双向抵达者与顶端抵达者进行匹配。