A multi-agent reinforcement learning approach for system-level flight delay absorption
With increasing air traffic, there is an ever-growing need for Air Traffic Controllers (ATCO) to efficiently manage traffic and congestion. Congestion often leads to increased delays in the Terminal Maneuvering Area (TMA), causing large amounts of fuel burn and detrimental environmental impacts. App...
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Main Authors: | , , |
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格式: | Conference or Workshop Item |
語言: | English |
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2023
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在線閱讀: | https://hdl.handle.net/10356/160172 https://dl.acm.org/conference/wsc |
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