Pricing problems with Thompson sampling - Lee, Samuel Wai Leong (2019)
In 1933, William R. Thompson proposed an algorithm known as Thompson sampling in order to maximise culmulative payo in a multi-armed bandit (MAB) problem. MAB problems have been fre- quently used to model real-life decision making scenarios. This pa- per explores the extension of Thompson sampling to other problems beyond the MAB setting. More speci cally, Thompson sampling is applied to product sales using data from a real dataset in a dynamic pricing setting as part of the multi-product pricing problem.