While the auto-bidding literature predominantly considers independent bidding, we investigate the coordination problem among multiple auto-bidders in online advertising platforms. Two motivating scenarios are: collaborative bidding among multiple bidders managed by a third-party bidding agent, and strategic bid selection for multiple ad campaigns managed by a single advertiser. We formalize this coordination problem as a theoretical model and investigate the coordination mechanism where only the highest-value bidder competes with outside bidders, while other coordinated bidders refrain from competing. We demonstrate that such a coordination mechanism dominates independent bidding, improving both Return-on-Spend (RoS) compliance and the total value accrued for the participating auto-bidders or ad campaigns, for a broad class of auto-bidding algorithms. Additionally, our simulations on synthetic and real-world datasets support the theoretical result that coordination outperforms independent bidding. These findings highlight both the theoretical potential and the practical robustness of coordinated auto-bidding in online auctions.

翻译：尽管自动竞价领域的研究主要关注独立竞价行为，本文探讨了在线广告平台中多个自动竞价者之间的协调问题。两个典型应用场景包括：由第三方竞价代理管理的多个竞拍者之间的协作竞价，以及单个广告主管理的多个广告活动的策略性出价选择。我们将此协调问题形式化为理论模型，并研究一种协调机制：在该机制下，仅最高价值竞拍者与外部竞拍者竞争，而其他协调竞拍者则避免参与竞争。我们证明，对于广泛的自动竞价算法类别，此类协调机制均优于独立竞价策略，既能提升支出回报率（RoS）的合规性，又能增加参与协调的自动竞价者或广告活动的总价值。此外，我们在合成数据集和真实数据集上的仿真实验也支持协调机制优于独立竞价的理论结论。这些发现共同揭示了协调式自动竞价在在线拍卖中的理论潜力与实践鲁棒性。