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GSP Auctions with Correlated Types

机译：相关类型的GSP拍卖

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摘要

The Generalized Second Price (GSP) auction is the primary method by which sponsered search advertisements are sold. We study the performance of this auction in the Bayesian setting for players with correlated types. Correlation arises very naturally in the context of sponsored search auctions, especially as a result of uncertainty inherent in the behaviour of the underlying ad allocation algorithm. We demonstrate that the Bayesian Price of Anarchy of the GSP auction is bounded by 4, even when agents have arbitrarily correlated types. Our proof highlights a connection between the GSP mechanism and the concept of smoothness in games, which may be of independent interest. For the special case of uncorrelated (i.e. independent) agent types, we improve our bound to 2(1 - 1/e)~(-1) ≈ 3.16, significantly improving upon previously known bounds. Using our techniques, we obtain the same bound on the performance of GSP at coarse correlated equilibria, which captures (for example) a repeated-auction setting in which agents apply regret-minimizing bidding strategies. Moreoever, our analysis is robust against the presence of irrational bidders and settings of asymmetric information, and our bounds degrade gracefully when agents apply strategies that form only an approximate equilibrium.
机译：广义第二价（GSP）拍卖是出售搜索广告的主要方法。我们研究了贝叶斯环境中具有相关类型的玩家的这次拍卖的表现。在赞助搜索拍卖的情况下，相关性非常自然地出现，特别是由于底层广告分配算法的行为固有的不确定性。我们证明，即使代理商具有任意相关的类型，GSP拍卖的无政府状态贝叶斯价格也受4限制。我们的证明凸显了GSP机制与游戏中的流畅性概念之间的联系，这可能与个人利益有关。对于不相关（即独立）代理类型的特殊情况，我们将绑定提高到2（1-1 / e）〜（-1）≈3.16，大大提高了先前已知的绑定范围。使用我们的技术，我们可以在粗略相关的均衡条件下获得与GSP绩效相同的界限，这可以捕获（例如）代理商采用后悔最小化出价策略的重复拍卖设置。而且，我们的分析对于不合理的竞标者的存在和不对称信息的设置是有力的，并且当代理人应用仅形成近似均衡的策略时，我们的界限会适度降低。

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