Distributed Agreement in the Arrovian Framework

TL;DR

This paper explores distributed preference aggregation, relaxing some classical voting axioms, and proves new impossibility results for approximate agreement tasks under various fault and system models.

Contribution

It introduces weaker distributed agreement tasks related to voting, and establishes novel impossibility results in both synchronous and asynchronous systems.

Findings

Impossibility results for $k$-set agreement and $\\epsilon$-approximate agreement.

Impossibility under weak assumptions for Kendall tau and Spearman metrics.

Extension of Arrow's framework to fault-tolerant distributed settings.

Abstract

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 $\epsilon$-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 $\epsilon$-approximate agreement task using the Kendall tau or Spearman footrule metrics holds under extremely weak assumptions.