Multi-Agent Deep Reinforcement Learning Based Resource Allocation for Ultra-Reliable Low-Latency Internet of Controllable Things
Author:
Affiliation:
1. Intelligent Perception and Computing Research Center, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
Funder
Ministry of Education-China Mobile Communications Group Co., Ltd (MoE-CMCC) Artificial Intelligence Project
Beijing University of Posts and Telecommunications Excellent Ph.D. Students Foundation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications
Link
http://xplorestaging.ieee.org/ielx7/7693/10214970/10014697.pdf?arnumber=10014697
Reference47 articles.
1. Resource Allocation in Information-Centric Wireless Networking With D2D-Enabled MEC: A Deep Reinforcement Learning Approach
2. A review of cooperative multi-agent deep reinforcement learning;oroojlooyjadid;arXiv 1908 03963,2019
3. Cooperative Multi-agent Control Using Deep Reinforcement Learning
4. A Comprehensive Survey of Multiagent Reinforcement Learning
5. Towards Energy Efficient Resource Allocation: When Green Mobile Edge Computing Meets Multi-Agent Deep Reinforcement Learning
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