Spiking Mean Field Multi-Agent Reinforcement Learning for Dynamic Resources Allocation in D2D Networks
Author:
Affiliation:
1. School of Computer Science and Cyber Engineering, Guangzhou University,Guangzhou,China
2. School of Computer Science and Engineering, Central South University,Changsha,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9719586/9718803/09719635.pdf?arnumber=9719635
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2. Deep reinforcement learning with population-coded spiking neural network for continuous control;tang;CoRR,2020
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Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. A brain-inspired theory of mind spiking neural network improves multi-agent cooperation and competition;Patterns;2023-08
2. S-MFRL: Spiking Mean Field Reinforcement Learning for Dynamic Resource Allocation of D2D Networks;IEEE Transactions on Vehicular Technology;2023-01
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