Best-of-Both-Worlds Fairness of the Envy-Cycle-Elimination Algorithm
Computer Science and Game Theory
2024-10-14 v1
Abstract
We consider the problem of fairly dividing indivisible goods among agents with additive valuations. It is known that an Epistemic EFX and -MMS allocation can be obtained using the Envy-Cycle-Elimination (ECE) algorithm. In this work, we explore whether this algorithm can be randomized to also ensure ex-ante proportionality. For two agents, we show that a randomized variant of ECE can compute an ex-post EFX and ex-ante envy-free allocation in near-linear time. However, for three agents, we show that several natural randomization methods for ECE fail to achieve ex-ante proportionality.
Cite
@article{arxiv.2410.08986,
title = {Best-of-Both-Worlds Fairness of the Envy-Cycle-Elimination Algorithm},
author = {Jugal Garg and Eklavya Sharma},
journal= {arXiv preprint arXiv:2410.08986},
year = {2024}
}