Improving Randomized Metric Distortion to 2.3282

📅 2026-08-29
📈 Citations: 0
Influential: 0
📄 PDF
🤖 AI Summary
本文通过引入随机大小稳定抽签方法,并结合综合否决机制,将随机化度量失真改进至2.3282。
📝 Abstract
In metric social choice, each voter ranks a set of $m$ candidates by her distance to them in an unknown metric space. The cost of a candidate is its average distance to the voters. A randomized voting rule must use only the rankings to choose a lottery over candidates. Its distortion is the worst-case ratio between the expected cost under the lottery it returns and the cost of the best candidate. Charikar, Ramakrishnan, Wang, and Wu [JACM 2024] prove an upper bound of $2.753$, establishing a constant separation from deterministic rules, for which the best achievable distortion is $3$. Independently, Frank [arXiv:2608.17863] and Ye [arXiv:2608.21202] improve the bound to $2.5$, using an equal mixture of maximal lottery and Integrated Veto. The existing arguments do not yield a better bound with any mixture of these rules. We break this barrier with a new ingredient, a random-size stable lottery. Let $D$ be a random variable over the domain of positive integers. A random-size stable lottery $\mathrm{RSL}_D$ guarantees that the probability of a random voter preferring any fixed candidate $c$ to her favorite of $D$ i.i.d. draws from $\mathrm{RSL}_D$ is at most $\mathbb{E}[1/(D+1)]$, where the probability also averages over $D$. When $D=k$ deterministically, this reduces to the stable $k$-lottery of Charikar, Ramakrishnan, Tan, and Wang [EC 2025]; the case $k=1$ is precisely a maximal lottery. Their minimax argument for a fixed $k$ easily generalizes to a random $D$. Our main contribution is to show how stability with respect to a random $D$ can be used to bound distortion. By mixing a suitably chosen random-size stable lottery with Integrated Veto, we get distortion at most $11641/5000=2.3282$. The proof combines infinite-dimensional conic linear-programming duality, heuristic nonlinear optimization, and exact rational verification via the Bernstein basis.
Problem

Research questions and friction points this paper is trying to address.

metric social choice
distortion
randomized voting rule
Innovation

Methods, ideas, or system contributions that make the work stand out.

random-size stable lottery
metric distortion
integrated veto
🔎 Similar Papers
No similar papers found.