Asymptotically Optimal Welfare of Posted Pricing for Multiple Items with MHR Distributions

Autor:	Braun, Alexander, Buttkus, Matthias, Kesselheim, Thomas
Rok vydání:	2021
Předmět:	Computer Science - Computer Science and Game Theory Computer Science - Data Structures and Algorithms
Druh dokumentu:	Working Paper
Popis:	We consider the problem of posting prices for unit-demand buyers if all $n$ buyers have identically distributed valuations drawn from a distribution with monotone hazard rate. We show that even with multiple items asymptotically optimal welfare can be guaranteed. Our main results apply to the case that either a buyer's value for different items are independent or that they are perfectly correlated. We give mechanisms using dynamic prices that obtain a $1 - \Theta \left( \frac{1}{\log n}\right)$-fraction of the optimal social welfare in expectation. Furthermore, we devise mechanisms that only use static item prices and are $1 - \Theta \left( \frac{\log\log\log n}{\log n}\right)$-competitive compared to the optimal social welfare. As we show, both guarantees are asymptotically optimal, even for a single item and exponential distributions. Comment: To appear at the 29th Annual European Symposium on Algorithms (ESA 2021)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2107.00526 Zobrazit plný text záznamu View this record from Arxiv