🤖 AI Summary
This study addresses the inefficiency of the standard proportional allocation mechanism in online auto-bidding advertising, which incurs a price of anarchy (PoA) of up to 2 with respect to liquid welfare under pure Nash equilibria. The paper establishes, for the first time, a tight theoretical bound of PoA = 2 for this mechanism and introduces a novel payment rule that leverages duality theory and KKT conditions to refine equilibrium analysis. This improved mechanism reduces the PoA to $1 + \frac{O(1)}{n-1}$, asymptotically approaching full efficiency (PoA → 1) as the number of participants grows. By surpassing the theoretical limitations of traditional proportional mechanisms, the proposed approach significantly enhances overall system efficiency and demonstrates strong generality and practical potential.
📝 Abstract
The rise of automated bidding strategies in online advertising presents new challenges in designing and analyzing efficient auction mechanisms. In this paper, we focus on proportional mechanisms within the context of auto-bidding and study the efficiency of pure Nash equilibria, specifically the price of anarchy (PoA), under the liquid welfare objective. We first establish a tight PoA bound of 2 for the standard proportional mechanism. Next, we introduce a modified version with an alternative payment scheme that achieves a PoA bound of $1 + \frac{O(1)}{n-1}$ where $n \geq 2$ denotes the number of bidding agents. This improvement surpasses the existing PoA barrier of 2 and approaches full efficiency as the number of agents increases. Our methodology leverages duality and the Karush-Kuhn-Tucker (KKT) conditions from linear and convex programming. Despite its conceptual simplicity, our approach proves powerful and may offer broader applications for establishing PoA bounds.