arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1907.02583cs.GT
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通过信息保留实现公平分割

Fair Division through Information Withholding

Hadi Hosseini, Sujoy Sikdar, Rohit Vaish, Jun Wang, Lirong Xia

摘要:

直到一个好的无嫉妒(EF1)是一个研究得很好的公平概念,用于不可分割的商品,通过移除最多一个好的来解决成对嫉妒。在最坏的情况下,每对代理人可能需要(假设)移除不同的商品,导致弱的总担保。我们研究的分配,几乎是免费的总量,并定义了一个新的公平性概念的基础上的信息扣留。根据这一概念,代理人可以扣留(或隐藏)其捆绑中的一些货物,并向其他代理人展示剩余的货物。我们注意到,在实践中,只要总体上保留少量的商品,就可以实现无嫉妒。我们发现,即使对于高度限制的估值类别,找到保留最佳数量的商品的分配在计算上也是困难的。与最坏情况下的结果相反,我们对合成和真实世界偏好数据的实验表明,现有的EF1分配算法保留了接近最优的商品数量。

英文摘要:

Envy-freeness up to one good (EF1) is a well-studied fairness notion for indivisible goods that addresses pairwise envy by the removal of at most one good. In the worst case, each pair of agents might require the (hypothetical) removal of a different good, resulting in a weak aggregate guarantee. We study allocations that are nearly envy-free in aggregate, and define a novel fairness notion based on information withholding. Under this notion, an agent can withhold (or hide) some of the goods in its bundle and reveal the remaining goods to the other agents. We observe that in practice, envy-freeness can be achieved by withholding only a small number of goods overall. We show that finding allocations that withhold an optimal number of goods is computationally hard even for highly restricted classes of valuations. In contrast to the worst-case results, our experiments on synthetic and real-world preference data show that existing algorithms for finding EF1 allocations withhold close-to-optimal number of goods.

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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