跳到正文
研踪PaperTrail

YOUR RESEARCH, IN SIGHT

让下一篇重要论文,不再错过。

覆盖计算机全学科,以 AI 为快捷入口。关注方向、作者和关键词,把发现变成持续的研究积累。

部分采集异常
正在读取账号与研究记录…

全站更新概况

+0新增论文
+0其中 AI 相关
+2已有论文修订
+100新增 AI 导读

arXiv 最近完成扫描:2026-11-08 16:36 · 全站最近入库:2026-11-08 06:02各信源进度 →

统计口径与数据新鲜度

统计 2026-11-07 17:21 — 2026-11-08 17:21(北京时间) · 点击数字查看对应简报;AI 相关包含在新增论文内。

最近完成检查:2026-11-08 16:36最近发现新增版本:2026-11-08 06:02库内论文最新更新时间:2026-11-06 02:59

每分钟刷新已保存的数据。空检查不代表采集异常;新收录可能包含历史论文。AI 导读按新增版本计数。

17,100 已收录论文14,661 AI 相关4,057 有修订112 HF 社区发现

浏览论文库

时间范围跟随排序:版本更新、本站收录或首次发表。最新收录可能包含历史论文。部分信源异常,查看状态 →

找到 1 篇论文 · 按版本更新时间排序上轮扫描起点 2026-11-08 16:33(北京时间)
新论文 · v1arXiv:2611.05505

The Power and Limits of Money Burning in Bilateral Trade

Moshe Babaioff, Noam Nisan, Ariel Shaulker

原文摘要

We study the power of money burning in bilateral trade. In this problem, a seller owns an indivisible item, a buyer would like to acquire it, and each of these two traders has a private value for the item and the values are sampled from independent distributions. We ask whether the traders can benefit from a mechanism that burns money, that is, one that charges the buyer more than it pays the seller, so that neither trader enjoys the difference (money burnt is a loss for the traders). Is it possible that the traders will ever be better off if the trade mechanism can burn money? For Bayesian incentive-compatible mechanisms and for deterministic dominant-strategy incentive-compatible (DSIC) mechanisms, it is known that money burning is always a waste and can only hurt the traders. Maybe surprisingly, we show that once a DSIC mechanism can use randomization, money burning can significantly benefit the traders, and the gain of each of them can be arbitrarily large. In contrast, we show that the power of DSIC randomized mechanisms that burn money is still very limited in the sense that they cannot guarantee any constant fraction of the first-best gains-from-trade.

cs.GT