Sample-efficient multi-agent reinforcement learning with masked reconstruction

Deep reinforcement learning (DRL) is a powerful approach that combines reinforcement learning (RL) and deep learning to address complex decision-making problems in high-dimensional environments. Although DRL has been remarkably successful, its low sample efficiency necessitates extensive training ti...

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Detalles Bibliográficos
Autores principales: Kim, Jung In, Lee, Young Jae, Heo, Jongkook, Park, Jinhyeok, Kim, Jaehoon, Lim, Sae Rin, Jeong, Jinyong, Kim, Seoung Bum
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10501567/
https://www.ncbi.nlm.nih.gov/pubmed/37708154
http://dx.doi.org/10.1371/journal.pone.0291545

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10501567/
https://www.ncbi.nlm.nih.gov/pubmed/37708154
http://dx.doi.org/10.1371/journal.pone.0291545

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