发表机构
Northwestern University（西北大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文综述拍卖的鲁棒设计，以最坏情况性能比量化鲁棒性，涵盖福利、收入及交易收益目标，并指出揭示原理在鲁棒机制设计中存在可量化的揭示差距。
AI 中文摘要
本文综述了拍卖的鲁棒设计与分析，重点关注计算机科学文献中的主流范式，该范式通过最坏情况下（相对于环境）鲁棒拍卖性能与针对该环境的最优拍卖性能之比来量化鲁棒性。应用包括对典型拍卖（如以福利为目标的一价拍卖）的鲁棒分析、以收入为目标的先验鲁棒拍卖设计，以及以交易收益为目标的先验鲁棒交换机制设计。最后，揭示原理在鲁棒机制设计中并非无损失。潜在损失可通过揭示差距来量化，即当从所有机制限制到揭示机制时所损失的鲁棒最优保证的比例。
英文摘要
The article reviews the robust design and analysis of auctions, focusing on the predominant paradigm in the computer science literature, which quantifies robustness by the worst-case, over environments, ratio between the robust auction's performance and that of an optimal auction for the environment. Applications include robust analysis of canonical auctions such as the first-price auction for the welfare objective, prior-robust auction design for the revenue objective, and prior-robust design of exchange mechanisms for the gains-from-trade objective. Finally, the revelation principle is not without loss in robust mechanism design. The potential loss can be quantified by the revelation gap, the fraction of the optimal robust guarantee that is lost when restricting from all mechanisms to revelation mechanisms.
CommentsThis is a preprint of a review article that is accepted to appear in the Annual Review of Economics in August of 2027. It contains an additional section on the revelation gap that, for space reasons, was mostly removed from the published version
