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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...
Autores principales: | Kravaris, Theocharis, Lentzos, Konstantinos, Santipantakis, Georgios, Vouros, George A., Andrienko, Gennady, Andrienko, Natalia, Crook, Ian, Garcia, Jose Manuel Cordero, Martinez, Enrique Iglesias |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
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 |
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