Robust multi-item auction design using statistical learning: Overcoming uncertainty in bidders' types distributions

• URL: http://arxiv.org/abs/2302.00941v1
• Date: Thu, 2 Feb 2023 08:32:55 GMT
• Title: Robust multi-item auction design using statistical learning: Overcoming uncertainty in bidders' types distributions
• Authors: Jiale Han and Xiaowu Dai
• Abstract summary: Our proposed approach utilizes nonparametric density estimation to accurately estimate bidders' types from historical bids. To further enhance efficiency of our mechanism, we introduce two novel strategies for query reduction. Simulation experiments conducted on both small-scale and large-scale data demonstrate that our mechanism consistently outperforms existing methods in terms of revenue design and query reduction.
• Score: 6.5920927560926295
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper presents a novel mechanism design for multi-item auction settings with uncertain bidders' type distributions. Our proposed approach utilizes nonparametric density estimation to accurately estimate bidders' types from historical bids, and is built upon the Vickrey-Clarke-Groves (VCG) mechanism, ensuring satisfaction of Bayesian incentive compatibility (BIC) and $\delta$-individual rationality (IR). To further enhance the efficiency of our mechanism, we introduce two novel strategies for query reduction: a filtering method that screens potential winners' value regions within the confidence intervals generated by our estimated distribution, and a classification strategy that designates the lower bound of an interval as the estimated type when the length is below a threshold value. Simulation experiments conducted on both small-scale and large-scale data demonstrate that our mechanism consistently outperforms existing methods in terms of revenue maximization and query reduction, particularly in large-scale scenarios. This makes our proposed mechanism a highly desirable and effective option for sellers in the realm of multi-item auctions.

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