A tractable online learning algorithm for the multinomial logit contextual bandit

•This work considers the dynamic assortment optimization problem.•The consumer choice is modelled via Multinomial logit contextual model.•The worst-case regret bound is free from the multiplicative problem dependent factor k and improves upon the previous bounds in the literature.•The k factor could...

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Vydané v:	European journal of operational research Ročník 310; číslo 2; s. 737 - 750
Hlavní autori:	Agrawal, Priyank, Tulabandhula, Theja, Avadhanula, Vashist
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 16.10.2023
Predmet:	Multi-armed bandit Multinomial logit model OR in marketing Revenue management Sequential decision-making OR in marketing Revenue management Sequential decision-making Multi-armed bandit Multinomial logit model
ISSN:	0377-2217, 1872-6860
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