A simulation-deep reinforcement learning (SiRL) approach for epidemic control optimization

In this paper, we address the controversies of epidemic control planning by developing a novel Simulation-Deep Reinforcement Learning (SiRL) model. COVID-19 reminded constituents over the world that government decision-making could change their lives. During the COVID-19 pandemic, governments were c...

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Detalles Bibliográficos
Autores principales: Bushaj, Sabah, Yin, Xuecheng, Beqiri, Arjeta, Andrews, Donald, Büyüktahtakın, İ. Esra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9512996/
https://www.ncbi.nlm.nih.gov/pubmed/36187178
http://dx.doi.org/10.1007/s10479-022-04926-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9512996/
https://www.ncbi.nlm.nih.gov/pubmed/36187178
http://dx.doi.org/10.1007/s10479-022-04926-7

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