A multi-agent reinforcement learning approach for system-level flight delay absorption

• المؤلفون الرئيسيون: Malhotra, Kanupriya, Lim, Zhi Jun, Alam, Sameer
• مؤلفون آخرون: 2022 Winter Simulation Conference
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling; Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence; Engineering::Aeronautical engineering::Air navigation; Multi-Agent; Reinforcement Learning; Extended Arrival Management; Air Traffic Management
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/160172; https://dl.acm.org/conference/wsc

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...