Pricing problems with Thompson sampling

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 sampl...

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Main Author: Lee, Samuel Wai Leong
Other Authors: Yan Zhenzhen
Format: Final Year Project
Language:English
Published: 2019
Subjects:
Online Access:http://hdl.handle.net/10356/77144
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-771442023-02-28T23:12:11Z Pricing problems with Thompson sampling Lee, Samuel Wai Leong Yan Zhenzhen School of Physical and Mathematical Sciences DRNTU::Science::Mathematics::Statistics 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. Bachelor of Science in Mathematical Sciences 2019-05-13T13:47:13Z 2019-05-13T13:47:13Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77144 en 30 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Science::Mathematics::Statistics
spellingShingle DRNTU::Science::Mathematics::Statistics
Lee, Samuel Wai Leong
Pricing problems with Thompson sampling
description 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.
author2 Yan Zhenzhen
author_facet Yan Zhenzhen
Lee, Samuel Wai Leong
format Final Year Project
author Lee, Samuel Wai Leong
author_sort Lee, Samuel Wai Leong
title Pricing problems with Thompson sampling
title_short Pricing problems with Thompson sampling
title_full Pricing problems with Thompson sampling
title_fullStr Pricing problems with Thompson sampling
title_full_unstemmed Pricing problems with Thompson sampling
title_sort pricing problems with thompson sampling
publishDate 2019
url http://hdl.handle.net/10356/77144
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