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arXiv 2209.03286cs.GT
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动态不可分项的公平分配(连续)

Fairly Allocating (Contiguous) Dynamic Indivisible Items with Few Adjustments

Mingwei Yang

摘要:

研究了在保证分配始终公平的条件下,将$T$不可分项动态分配给$n$代理的问题.由于分配不可撤销时实现公平性的负面结果,我们允许调整以实现公平性,目标是最小化调整次数。对于有限的添加剂或一般相同的估值,我们表明,羡慕免费一个项目(EF1)可以实现没有调整。对于加法估值,我们给出了一个EF1算法,需要$O(mT)$调整,改善以前的结果$O(nmT)$调整,其中$m$是所有代理之间的项目的不同估值的最大数量。我们进一步对项目施加邻接约束,使项目按到达顺序排列在一条线上,并要求每个代理获得连续的项目块。我们提出了广泛的结果,以实现与添加剂近似因子(PROPa)或EF1,其中PROPa是一个较弱的公平性概念比EF1的比例。特别是,我们发现,对于相同的估值,实现PROPa需要$Θ(nT)$调整。此外,我们表明,这是无望的,无论是PROPa或EF1的估值是不相同的任何显着改善。我们的研究结果表现出很大的差异,在连续和非连续的设置相同和不相同的情况下。我们所有的正结果在计算上都是有效的。

英文摘要:

We study the problem of dynamically allocating $T$ indivisible items to $n$ agents with the restriction that the allocation is fair all the time. Due to the negative results to achieve fairness when allocations are irrevocable, we allow adjustments to make fairness attainable with the objective to minimize the number of adjustments. For restricted additive or general identical valuations, we show that envy-freeness up to one item (EF1) can be achieved with no adjustments. For additive valuations, we give an EF1 algorithm that requires $O(mT)$ adjustments, improving the previous result of $O(nmT)$ adjustments, where $m$ is the maximum number of different valuations for items among all agents. We further impose the contiguity constraint on items such that items are arranged on a line by the order they arrive and require that each agent obtains a consecutive block of items. We present extensive results to achieve either proportionality with an additive approximate factor (PROPa) or EF1, where PROPa is a weaker fairness notion than EF1. In particular, we show that for identical valuations, achieving PROPa requires $Θ(nT)$ adjustments. Moreover, we show that it is hopeless to make any significant improvement for either PROPa or EF1 when valuations are nonidentical. Our results exhibit a large discrepancy between the identical and nonidentical cases in both contiguous and noncontiguous settings. All our positive results are computationally efficient.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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