Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/77144
Title: Pricing problems with Thompson sampling
Authors: Lee, Samuel Wai Leong
Keywords: DRNTU::Science::Mathematics::Statistics
Issue Date: 2019
Abstract: 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.
URI: http://hdl.handle.net/10356/77144
Schools: School of Physical and Mathematical Sciences 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Student Reports (FYP/IA/PA/PI)

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