NeurIPS 2019poster21 citations
Optimal Pricing in Repeated Posted-Price Auctions with Different Patience of the Seller and the Buyer
Arsenii Vanunts, Alexey Drutsa
Abstract
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.
BibTeX
@inproceedings{NEURIPS2019_33e8075e,
author = {Vanunts, Arsenii and Drutsa, Alexey},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Optimal Pricing in Repeated Posted-Price Auctions with Different Patience of the Seller and the Buyer},
url = {https://proceedings.neurips.cc/paper_files/paper/2019/file/33e8075e9970de0cfea955afd4644bb2-Paper.pdf},
volume = {32},
year = {2019}
}