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arXiv 2409.04685cs.DCcs.GT
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阿罗框架中的分布式一致性

Distributed Agreement in the Arrovian Framework

Kenan Wood, Hammurabi Mendes, Jonad Pulaj

AI总结:

本文将阿罗不可能性定理置于含崩溃故障的分布式语境,研究放宽为 $k$-set agreement 或 $ε$-approximate agreement 的偏好聚合任务,并证明同步与异步系统中的多项不可能性结果。

摘要:

偏好聚合是投票理论中的一个基本问题,其中必须将一组备选方案的公开输入排序(称为偏好)聚合为满足某种合理性属性的单一偏好。著名的阿罗不可能性定理等价于同步无故障系统中的一项分布式任务,该系统满足尊重一致偏好、保持无关备选方案独立性(IIA)和非独裁等属性,同时还要满足共识,因为只能决定一个偏好。在本工作中,我们研究一项更弱的分布式任务,其中引入了崩溃故障,不再要求 IIA,并且共识属性被放宽为使用偏好集合上任意度量的 $k$-set agreement 或 $ε$-approximate agreement。特别地,我们在同步和异步分布式系统中证明了关于这两项任务的若干新颖不可能性结果。我们还表明,在使用 Kendall tau 或 Spearman footrule 度量时,我们的 $ε$-approximate agreement 任务的不可能性在极弱假设下仍然成立。

英文摘要:

Preference aggregation is a fundamental problem in voting theory, in which public input rankings of a set of alternatives (called preferences) must be aggregated into a single preference that satisfies certain soundness properties. The celebrated Arrow Impossibility Theorem is equivalent to a distributed task in a synchronous fault-free system that satisfies properties such as respecting unanimous preferences, maintaining independence of irrelevant alternatives (IIA), and non-dictatorship, along with consensus since only one preference can be decided. In this work, we study a weaker distributed task in which crash faults are introduced, IIA is not required, and the consensus property is relaxed to either $k$-set agreement or $ε$-approximate agreement using any metric on the set of preferences. In particular, we prove several novel impossibility results for both of these tasks in both synchronous and asynchronous distributed systems. We additionally show that the impossibility for our $ε$-approximate agreement task using the Kendall tau or Spearman footrule metrics holds under extremely weak assumptions.

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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