Explaining deep reinforcement learning decisions in complex multiagent settings: towards enabling automation in air traffic flow management

With the objective to enhance human performance and maximize engagement during the performance of tasks, we aim to advance automation for decision making in complex and large-scale multi-agent settings. Towards these goals, this paper presents a deep multi agent reinforcement learning method for res...

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Detalles Bibliográficos
Autores principales: Kravaris, Theocharis, Lentzos, Konstantinos, Santipantakis, Georgios, Vouros, George A., Andrienko, Gennady, Andrienko, Natalia, Crook, Ian, Garcia, Jose Manuel Cordero, Martinez, Enrique Iglesias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169601/
https://www.ncbi.nlm.nih.gov/pubmed/35694685
http://dx.doi.org/10.1007/s10489-022-03605-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9169601/
https://www.ncbi.nlm.nih.gov/pubmed/35694685
http://dx.doi.org/10.1007/s10489-022-03605-1

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