通过共识估计、交叉检查和利润提取的机制设计
Mechanism Design via Consensus Estimates, Cross Checking, and Profit Extraction
摘要：
只有一种无先验最优机制设计技术，它超越了数字商品的结构性良性设置。该技术使用随机抽样来估计代理值的分布，然后采用贝叶斯最优机制来估计剩余玩家的分布。虽然相当普遍，即使是数字商品，这种随机抽样拍卖有一个复杂的分析，是已知的次优。为了克服这些问题，我们将Goldberg和Hartline（2003）的共识技术推广到结构丰富的环境，例如，专一的组合拍卖
英文摘要：
There is only one technique for prior-free optimal mechanism design that generalizes beyond the structurally benevolent setting of digital goods. This technique uses random sampling to estimate the distribution of agent values and then employs the Bayesian optimal mechanism for this estimated distribution on the remaining players. Though quite general, even for digital goods, this random sampling auction has a complicated analysis and is known to be suboptimal. To overcome these issues we generalize the consensus technique from Goldberg and Hartline (2003) to structurally rich environments that include, e.g., single-minded combinatorial auctions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
