Complex Task Assignment of Aviation Emergency Rescue Based on Multiagent Reinforcement Learning

Che Shen () and Xianbing Wang
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Che Shen: The Hong Kong University of Science and Technology
Xianbing Wang: Nanjing University of Aeronautics and Astronautics

Chapter Chapter 26 in City, Society, and Digital Transformation, 2022, pp 345-355 from Springer

Abstract: Abstract Emergency rescue is a powerful countermeasure to disasters, among which Aviation Emergency Rescue (AER) is irreplaceable thanks to its unique aviation attribute. However, traditional optimization methods are not capable of the dynamic task allocation of AER. This study performs a Multiagent Reinforcement Learning (MARL) model to handle the complex task assignment problem faced in AER, carries out a detailed analysis of the problem, and do comparative experiments with the Nearby policy and Best-fit policy. The result shows that the MARL model outperforms other simple models in AER.

Keywords: Aviation emergency rescue; Multiagent reinforcement learning; Complex task assignment (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-031-15644-1_26

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DOI: 10.1007/978-3-031-15644-1_26

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