Investigation of independent reinforcement learning algorithms in multi-agent environments

Independent reinforcement learning algorithms have no theoretical guarantees for finding the best policy in multi-agent settings. However, in practice, prior works have reported good performance with independent algorithms in some domains and bad performance in others. Moreover, a comprehensive stud...

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Detalles Bibliográficos
Autores principales: Lee, Ken Ming, Ganapathi Subramanian, Sriram, Crowley, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9530713/
https://www.ncbi.nlm.nih.gov/pubmed/36204598
http://dx.doi.org/10.3389/frai.2022.805823

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9530713/
https://www.ncbi.nlm.nih.gov/pubmed/36204598
http://dx.doi.org/10.3389/frai.2022.805823

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