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Latest revision as of 21:48, 3 February 2021
Abstract
We propose and implement a decentralized, intelligent air traffic flow management (ATFM) solution to improve the efficiency of air transportation in the ASEAN region as a whole. Our system, named BlockAgent, leverages the inherent synergy between multi-agent reinforcement learning (RL) for air traffic flow optimization; and the rising blockchain technology for a secure, transparent and decentralized coordination platform. As a result, BlockAgent does not require a centralized authority for effective ATFM operations. We have implemented several novel distributed coordination approaches for RL in BlockAgent. Empirical experiments with real air traffic data concerning regional airports have demonstrated the feasibility and effectiveness of our approach. To the best of our knowledge, this is the first work that considers blockchain-based, distributed RL for ATFM.
Original document
The different versions of the original document can be found in:
- https://ink.library.smu.edu.sg/sis_research/4647 under the license cc-by-nc-nd
Document information
Published on 01/01/2020
Volume 2020, 2020
DOI: 10.1109/indin41052.2019.8972225
Licence: Other
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