S-MFRL: Spiking Mean Field Reinforcement Learning for Dynamic Resource Allocation of D2D Networks
Author:
Affiliation:
1. School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, China
2. Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/25/10017140/09872041.pdf?arnumber=9872041
Reference41 articles.
1. Power Control for D2D Communication Using Multi-Agent Reinforcement Learning
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5. Counterfactual Multi-Agent Policy Gradients
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