Multi-Agent Mix Hierarchical Deep Reinforcement Learning for Large-Scale Fleet Management
Author:
Affiliation:
1. School of Information Engineering, East China Jiaotong University, Nanchang, China
2. Department of Science and Technology, University of Macau, Macau, China
Funder
National Natural Science Foundation of China
Natural Science Foundation of Jiangxi Province
Graduate Innovation Foundation of Jiangxi Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/10339106/10221776.pdf?arnumber=10221776
Reference36 articles.
1. Context-Aware Taxi Dispatching at City-Scale Using Deep Reinforcement Learning
2. Deep Reinforcement Learning with Knowledge Transfer for Online Rides Order Dispatching
3. Supply-Demand-aware Deep Reinforcement Learning for Dynamic Fleet Management
4. Monotonic value function factorisation for deep multi-agent reinforcement learning;rashid;J Mach Learn Res,2020
5. On the approximation of cooperative heterogeneous multi-agent reinforcement learning (MARL) using mean field control (MFC);mondal;J Mach Learn Res,2022
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