Self-Sustaining Multiple Access with Continual Deep Reinforcement Learning for Dynamic Metaverse Applications
Author:
Affiliation:
1. Oulu University,Oulu,Finland
2. Futurewei Technologies,USA
Funder
Academy of Finland
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10271705/10271778/10271915.pdf?arnumber=10271915
Reference16 articles.
1. Towards Continual Reinforcement Learning: A Review and Perspectives
2. A Survey of Reinforcement Learning Algorithms for Dynamically Varying Environments;padakandla;ACM Computing Surveys,2021
3. Deep Reinforcement Learning with Double Q-Learning
4. Q-learning
5. Multi-Agent Reinforcement Learning-Based Distributed Channel Access for Next Generation Wireless Networks
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