Hierarchical multiagent reinforcement learning for maritime traffic management

Hierarchical multiagent reinforcement learning for maritime traffic management

Increasing global maritime traffic coupled with rapid digitization and automation in shipping mandate developing next generation maritime traffic management systems to mitigate congestion, increase safety of navigation, and avoid collisions in busy and geographically constrained ports (such as Singa...

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Bibliographic Details
Main Authors: SINGH, Arambam James, KUMAR, Akshat, LAU, Hoong Chuin
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2020
Subjects:
Autonomous agents
Multi agent systems
Reinforcement learning
Service vessels
Waterway transportation
Artificial Intelligence and Robotics
Operations Research, Systems Engineering and Industrial Engineering
Transportation
Online Access:https://ink.library.smu.edu.sg/sis_research/5403
https://ink.library.smu.edu.sg/context/sis_research/article/6406/viewcontent/p1278.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/5403
https://ink.library.smu.edu.sg/context/sis_research/article/6406/viewcontent/p1278.pdf

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