中文

加权公平分配的渐近分析

计算机科学与博弈论 2025-09-16 v1 离散数学 概率论

摘要

Several resource allocation settings involve agents with unequal entitlements represented by weights. We analyze weighted fair division from an asymptotic perspective: if mm items are divided among nn agents whose utilities are independently sampled from a probability distribution, when is it likely that a fair allocation exist? We show that if the ratio between the weights is bounded, a weighted envy-free allocation exists with high probability provided that m=Ω(nlogn/loglogn)m = \Omega(n\log n/\log\log n), generalizing a prior unweighted result. For weighted proportionality, we establish a sharp threshold of m=n/(1μ)m = n/(1-\mu) for the transition from non-existence to existence, where μ(0,1)\mu\in (0,1) denotes the mean of the distribution. In addition, we prove that for two agents, a weighted envy-free (and weighted proportional) allocation is likely to exist if m=ω(r)m = \omega(\sqrt{r}), where rr denotes the ratio between the two weights.

关键词

引用

@article{arxiv.2504.21728,
  title  = {Asymptotic Analysis of Weighted Fair Division},
  author = {Pasin Manurangsi and Warut Suksompong and Tomohiko Yokoyama},
  journal= {arXiv preprint arXiv:2504.21728},
  year   = {2025}
}

备注

Appears in the 34th International Joint Conference on Artificial Intelligence (IJCAI), 2025