Derandomization of auctions

• 成果类型: Article
• 署名作者: Aggarwal, Gagan; Fiat, Amos; Goldberg, Andrew V.; Hartline, Jason D.; Immorlica, Nicole; Sudan, Madhu
• 署名单位: Northwestern University; Alphabet Inc.; Google Incorporated; Tel Aviv University; Massachusetts Institute of Technology (MIT)
• 刊物名称: GAMES AND ECONOMIC BEHAVIOR
• ISSN/ISSBN: 0899-8256
• DOI: 10.1016/j.geb.2010.07.007
• 发表日期: 2011
• 页码: 1-11
• 关键词: Auctions; randomization; Prior-free; Hat puzzles

摘要

We study the role of randomization in seller optimal (i.e., profit maximization) auctions. Bayesian optimal auctions (e.g., Myerson, 1981) assume that the valuations of the agents are random draws from a distribution and prior-free optimal auctions either are randomized (e.g.. Goldberg et al., 2006) or assume the valuations are randomized (e.g., Segal, 2003). Is randomization fundamental to profit maximization in auctions? Our main result is a general approach to derandomize single-item multi-unit unit-demand auctions while approximately preserving their performance (i.e., revenue). Our general technique is constructive but not computationally tractable. We complement the general result with the explicit and computationally-simple derandomization of a particular auction. Our results are obtained through analogy to hat puzzles that are interesting in their own right. (C) 2010 Elsevier Inc. All rights reserved.