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：尽管自动投标文献主要考虑独立投标，我们研究了在线广告平台中多个自动投标者间的协调问题。两个典型场景包括：由第三方投标代理管理的多个投标者进行协作投标，以及单个广告主为多个广告活动进行策略性投标选择。我们将该协调问题形式化为理论模型，并研究了一种协调机制——在该机制中，仅最高价值投标者与外部投标者竞争，而其他协调投标者则放弃竞争。我们证明，对于一大类自动投标算法，该协调机制优于独立投标，能同时提升投资回报率（RoS）合规性以及参与投标的自动投标者或广告活动所获得的总价值。此外，在合成数据集和真实数据集上的模拟实验支持了理论结果：协调投标优于独立投标。这些发现凸显了在线拍卖中协调自动投标的理论潜力与实践稳健性。