Determination of optimal prevention strategy for COVID-19 based on multi-agent simulation

DOI10.1007/S42081-022-00163-1OpenAlexW4282835306MaRDI QIDQ2166049

Yuki Yoshida, Yoshitake Kitanishi, Satoki Fujita, Ryo Kiguchi

Publication date: 23 August 2022

Published in: Japanese Journal of Statistics and Data Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s42081-022-00163-1

zbMATH Keywords

heterogeneityreinforcement learningmulti-agent simulationCOVID-19

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Special feature: Statistics for COVID-19 pandemic data

Cites Work

• \({\mathcal Q}\)-learning

This page was built for publication: Determination of optimal prevention strategy for COVID-19 based on multi-agent simulation