2021/10/11 by Zhanhao Zhang, Zhang, Zhanhao · 3 citations
Business, Management and Accounting · Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Artificial intelligence #Auction Theory and Applications #Computer science #Consumer Market Behavior and Pricing #Data science #Deep learning #Economics #Mechanism (biology) #Mechanism design #Microeconomics #cs.GT #cs.LG
paper · pdf · doi:10.48550/arxiv.2110.06880
published in arXiv (Cornell University) (Cornell University)
arxiv created 2021/10/11 · openalex publication_date 2021/10/11 · arxiv updated 2021/10/14 · openalex created_date 2021/10/25 · openalex updated_date 2026/07/28
Online auction has been very widespread in the recent years. Platform administrators are working hard to refine their auction mechanisms that will generate high profits while maintaining a fair resource allocation. With the advancement of computing technology and the bottleneck in theoretical frameworks, researchers are shifting gears towards online auction designs using deep learning approaches. In this article, we summarized some common deep learning infrastructures adopted in auction mechanism designs and showed how these architectures are evolving. We also discussed how researchers are tackling with the constraints and concerns in the large and dynamic industrial settings. Finally, we pointed out several currently unresolved issues for future directions.