Enhancing Affine Maximizer Auctions with Correlation-Aware Payment

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The latest research proposes an improved affine maximization auction mechanism, which optimizes the auction outcome by introducing payment rules based on correlation perception. This approach aims to address the efficiency losses caused by the lack of consideration for correlations among bidders in traditional affine maximization auctions, thereby improving overall social welfare and resource allocation efficiency.

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A arXiv cs.LG en 2026-09-07 12:00

本文提出一种名为 Correlation-Aware AMA（CA-AMA）的新框架，通过引入关联感知支付机制增强 Affine Maximizer Auctions（AMAs），旨在解决传统 AMA 在竞拍者估值相关分布下表达力受限的问题。研究证明 CA-AMA 保持占优策略激励相容性（DSIC），并将最优 CA-AMA 的求解形式化为受个体理性（IR）约束的优化问题。理论分析表明，经典 AMAs 在某些场景下收益可能任意差，而 CA-AMA 可达到最优收益；为此设计了包含目标函数连续性推导及偏离严格 IR 偏差泛化界定的两阶段训练算法。实验结果显示，该算法能在多种分布中找到近似最优的 CA-AMA，实现收益提升且对 IR 的违反程度较低。