Non Stationary Multi-Armed Bandit: Empirical Evaluation of a New Concept Drift-Aware Algorithm

The Multi-Armed Bandit (MAB) problem has been extensively studied in order to address real-world challenges related to sequential decision making. In this setting, an agent selects the best action to be performed at time-step t, based on the past rewards received by the environment. This formulation...

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Detalles Bibliográficos
Autores principales: Cavenaghi, Emanuele, Sottocornola, Gabriele, Stella, Fabio, Zanker, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8004723/
https://www.ncbi.nlm.nih.gov/pubmed/33807028
http://dx.doi.org/10.3390/e23030380

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8004723/
https://www.ncbi.nlm.nih.gov/pubmed/33807028
http://dx.doi.org/10.3390/e23030380

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