Reserve Pricing in Repeated Second-Price Auctions with Strategic Bidders

Autor:	Drutsa, Alexey
Rok vydání:	2019
Předmět:	Computer Science - Computer Science and Game Theory Computer Science - Machine Learning Statistics - Machine Learning 91A20 68T05 68W27 91A05 91A26 I.2.6 F.2.2
Druh dokumentu:	Working Paper
Popis:	We study revenue optimization learning algorithms for repeated second-price auctions with reserve where a seller interacts with multiple strategic bidders each of which holds a fixed private valuation for a good and seeks to maximize his expected future cumulative discounted surplus. We propose a novel algorithm that has strategic regret upper bound of $O(\log\log T)$ for worst-case valuations. This pricing is based on our novel transformation that upgrades an algorithm designed for the setup with a single buyer to the multi-buyer case. We provide theoretical guarantees on the ability of a transformed algorithm to learn the valuation of a strategic buyer, which has uncertainty about the future due to the presence of rivals. Comment: 22 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1906.09331 Zobrazit plný text záznamu View this record from Arxiv