This paper studies multi-unit auctions powered by intermediaries, where each
intermediary owns a private set of unit-demand buyers and all intermediaries
are networked with each other. Our goal is to incentivize the intermediaries to
diffuse the auction information to individuals they can reach, including their
private buyers and neighboring intermediaries, so that more potential buyers
are able to participate in the auction. To this end, we build a diffusion-based
auction framework which incorporates the strategic interaction of
intermediaries. It is showed that the classic Vickrey-Clarke-Groves (VCG)
mechanism within the framework can achieve the maximum social welfare, but it
may decrease the seller's revenue or even lead to a deficit. To overcome the
revenue issue, we propose a novel auction, called critical neighborhood
auction, which not only maximizes the social welfare, but also improves the
seller's revenue comparing to the VCG mechanism with/without intermediaries.

本文研究了由中介机构驱动的多单位拍卖，其中每个中介机构拥有一组单位需求买家，所有中介机构都网络化相互连接。研究目的是激励中介机构向其可以触及的个人（包括其私人买家和邻近的中介机构）传播拍卖信息，从而使更多的潜在买家能够参与拍卖，并在此基础上构建了一个基于扩散的拍卖框架，其中包括中介机构的战略互动。研究表明，在此框架内，经典的 Vickrey-Clarke-Groves（VCG）机制可以实现最大的社会福利，但可能会减少卖方的收益，甚至导致赤字。为了解决这个问题，我们提出了一种新型拍卖，称为关键邻域拍卖，不仅可以最大化社会福利，而且还可以改善对比带 / 不带中介机构的 VCG 机制的卖方收益。

带中介的多单位扩散拍卖

Multi-Unit Diffusion Auctions with Intermediaries

Sponsored search involves running an auction among advertisers who bid in
order to have their ad shown next to search results for specific keywords.
Currently, the most popular auction for sponsored search is the "Generalized
Second Price" (GSP) auction in which advertisers are assigned to slots in the
decreasing order of their "score," which is defined as the product of their bid
and click-through rate. In the past few years, there has been significant
research on the game-theoretic issues that arise in an advertiser's interaction
with the mechanism as well as possible redesigns of the mechanism, but this
ranking order has remained standard.
From a search engine's perspective, the fundamental question is: what is the
best assignment of advertisers to slots? Here "best" could mean "maximizing
user satisfaction," "most efficient," "revenue-maximizing," "simplest to
interact with," or a combination of these. To answer this question we need to
understand the behavior of a search engine user when she sees the displayed
ads, since that defines the commodity the advertisers are bidding on, and its
value. Most prior work has assumed that the probability of a user clicking on
an ad is independent of the other ads shown on the page.
We propose a simple Markovian user model that does not make this assumption.
We then present an algorithm to determine the most efficient assignment under
this model, which turns out to be different than that of GSP. A truthful
auction then follows from an application of the Vickrey-Clarke-Groves (VCG)
mechanism. Further, we show that our assignment has many of the desirable
properties of GSP that makes bidding intuitive. At the technical core of our
result are a number of insights about the structure of the optimal assignment.

通过研究用户行为，提出一种基于马尔可夫模型的最高效广告分配算法，结合 VCG 机制实现真实拍卖，得到了和 GSP 相似的拍卖稳定性和直观性。