We study revenue optimization pricing algorithms for repeated posted-price auctions where a seller interacts with a single strategic buyer that holds a fixed private valuation. When the participants non-equally discount their cumulative utilities, we show that the optimal constant pricing (which offers the Myerson price) is no longer optimal. In the case of more patient seller, we propose a novel multidimensional optimization functional --- a generalization of the one used to determine Myerson's price. This functional allows to find the optimal algorithm and to boost revenue of the optimal static pricing by an efficient low-dimensional approximation. Numerical experiments are provided to support our results.
Arsenii Vanunts (Yandex)
Alexey Drutsa (Yandex)
More from the Same Authors
2020 Workshop: Crowd Science Workshop: Remoteness, Fairness, and Mechanisms as Challenges of Data Supply by Humans for Automation »
Daria Baidakova · Fabio Casati · Alexey Drutsa · Dmitry Ustalov
2016 Poster: Efficient High-Order Interaction-Aware Feature Selection Based on Conditional Mutual Information »
Alexander Shishkin · Anastasia Bezzubtseva · Alexey Drutsa · Ilia Shishkov · Ekaterina Gladkikh · Gleb Gusev · Pavel Serdyukov