论文标题
公平的二元估值：统治所有人的规则
Fair Division with Binary Valuations: One Rule to Rule Them All
论文作者
论文摘要
我们研究代理商中不可分割的商品的公平分配。先前的研究重点是添加剂的偏好，这在寻求真实性，公平和效率时会导致不可能。我们表明，当代理具有二进制添加剂偏好时，一个引人注目的规则 - 最大NASH福利（MNW） - 提供了所有三种保证。 具体而言，我们表明，具有词典图案的确定性MNW除了嫉妒的最佳和帕累托的最佳状态外，还具有群体策略性。我们还证明，可以将分数MNW（已知是群体策略性，无嫉妒和帕累托的最佳选择）作为确定性MNW分配的分配，这是嫉妒的，最多是一种商品。我们的工作将最大的NASH福利确立为二进制添加剂偏好领域中的最终分配规则。
We study fair allocation of indivisible goods among agents. Prior research focuses on additive agent preferences, which leads to an impossibility when seeking truthfulness, fairness, and efficiency. We show that when agents have binary additive preferences, a compelling rule -- maximum Nash welfare (MNW) -- provides all three guarantees. Specifically, we show that deterministic MNW with lexicographic tie-breaking is group strategyproof in addition to being envy-free up to one good and Pareto optimal. We also prove that fractional MNW -- known to be group strategyproof, envy-free, and Pareto optimal -- can be implemented as a distribution over deterministic MNW allocations, which are envy-free up to one good. Our work establishes maximum Nash welfare as the ultimate allocation rule in the realm of binary additive preferences.
