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arXiv 2607.03463cs.GT
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随机串行独裁机制是$\sqrt{2}$-无嫉妒的

Random Serial Dictatorship is $\sqrt{2}$-Envy-Free

McGill University(麦吉尔大学);Indian Institute of Technology Bombay(印度理工学院孟买分校)

Frank Connor, Max Dupré la Tour, Louis-Roy Langevin, Vishnu V. Narayan, Ndiamé Ndiaye, Neil Rahman, Adrian Vetta

AI总结:

研究房屋分配问题中随机串行独裁机制(RSD)的公平性,通过嫉妒率量化其与无嫉妒的偏差,给出RSD是$\sqrt{2}$-无嫉妒的匹配上界,并分析其扩展机制在不同估值类下情况。

摘要:

我们分析房屋分配问题,其中一组代理必须与一组他们具有基数效用的对象相匹配。该问题的一个核心机制是随机串行独裁(RSD),由于其简单性和通过其属性的精确表征的存在,长期以来一直是研究的规范主题。尽管有这种广泛的理解,但关于这种机制公平性的一个基本定量问题仍未解决。虽然RSD通常被视为事前公平,但令人惊讶的是,它在期望中不是无嫉妒的。我们通过嫉妒率来量化其与无嫉妒的偏差,嫉妒率是所有实例和代理对中代理对另一个代理的随机对象的期望效用与其自己的随机对象的期望效用之比的最大值。先前的工作表明RSD的嫉妒率有一个$\sqrt{2}\approx1.414$的下界。我们的主要结果是一个匹配的上界,表明RSD在房屋分配问题中是$\sqrt{2}$-无嫉妒的。我们进一步分析了RSD的两个自然扩展(随机循环机制和迭代RSD机制)到代理和对象数量不相等以及更一般估值类的设置。对于加法估值,随机循环的这个比率增加到至少$1.5$且至多$1.707$,但迭代RSD仍然恰好是$\sqrt{2}$。对于次模估值,我们证明了两种机制的常数因子上界和下界,在两种情况下都只留下一个小的常数差距。对于更一般的XOS和次可加估值类,我们对两种机制进行了紧密分析,表明嫉妒率在代理数量上是无界的。这些结果为随机串行独裁及其自然推广近似无嫉妒的程度提供了第一个紧密或几乎紧密的定量保证。

英文摘要:

We analyze the house allocation problem, in which a set of agents must be matched to a set of objects for which they have cardinal utilities. A central mechanism for this problem is random serial dictatorship (RSD), which has long served as a canonical subject of study due to its simplicity and the existence of exact characterizations by its properties. Despite this extensive understanding, a basic quantitative question about the fairness of this mechanism remains unresolved. Although RSD is often viewed as fair ex ante, surprisingly, it is not envy-free in expectation. We quantify its deviation from envy-freeness via the envy-ratio, which is the maximum over all instances and pairs of agents of the ratio between an agent's expected utility for another agent's random object and for its own random object. Prior work shows a factor-$\sqrt{2}\approx 1.414$ lower bound on the envy-ratio of RSD. Our headline result is a matching upper bound, showing that RSD is $\sqrt{2}$-envy-free in the house allocation problem. We further analyze the two natural extensions of RSD (the randomized round-robin mechanism and the iterated-RSD mechanism) to settings with unequal numbers of agents and objects and more general valuation classes. For additive valuations, this ratio increases to at least $1.5$ and at most $1.707$ for randomized round-robin, but remains exactly $\sqrt{2}$ for iterated-RSD. For submodular valuations, we prove constant-factor upper and lower bounds for both mechanisms, leaving only a small constant gap in both cases. For the more general classes of XOS and subadditive valuations, we present a tight analysis for both mechanisms, showing that the envy-ratio is unbounded in the number of agents. These results provide the first tight or nearly tight quantitative guarantees on the extent to which random serial dictatorship and its natural generalizations approximate envy-freeness.

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