2019
NIPS
NeurIPS 2019
Optimal Pricing in Repeated Posted-Price Auctions with Different Patience of the Seller and the Buyer
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.
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning and Mathematics & Optimization
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Keyword Pioneer
— myerson price
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy
Authors
Topics
Machine Learning > Optimization & Theory > Optimization
Machine Learning > Application Areas > Risk Management
Mathematics & Optimization > Optimization > Stochastic Methods
Mathematics & Optimization > Optimization > Online Algorithms
Machine Learning > Learning Types > Multi-Agent Systems
Mathematics & Optimization > Optimization > Game Theory
Artificial Intelligence > Core AI > Game Theory