The MNL-Bandit Problem

Shipra Agrawal; Vashist Avadhanula; Vineet Goyal; Assaf Zeevi

doi:10.1007/978-3-031-01926-5_9

The MNL-Bandit Problem

Shipra Agrawal^*, Vashist Avadhanula, Vineet Goyal, Assaf Zeevi

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

1 Scopus citations

Abstract

In this chapter, we consider a dynamic assortment optimization problem where customers choose according to an unknown MNL choice model. In each period, we offer a subset (assortment) of products and observe the customer’s choice to learn the model parameters. We present two dynamic assortment selection approaches that optimally balances the exploration–exploitation trade-off and does not require any prior knowledge about the model parameters.

Original language	English
Title of host publication	Springer Series in Supply Chain Management
Publisher	Springer Nature
Pages	211-240
Number of pages	30
DOIs	https://doi.org/10.1007/978-3-031-01926-5_9
State	Published - 2022
Externally published	Yes

Publication series

Name	Springer Series in Supply Chain Management
Volume	18
ISSN (Print)	2365-6395
ISSN (Electronic)	2365-6409

Funding

Funders	Funder number
Columbia University

Access to Document

10.1007/978-3-031-01926-5_9

Cite this

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The MNL-Bandit Problem

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