Learning Generalized Wireless MAC Communication Protocols via Abstraction
Author:
Affiliation:
1. University of Catania,Department of Electrical, Electronics and Computer Engineering,Italy
2. University of Oulu,Centre for Wireless Communications,Finland
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10000063/10000593/10000805.pdf?arnumber=10000805
Reference11 articles.
1. State abstractions for lifelong reinforcement learning;abel;Proceedings of the 35th Inter-national Conference on Machine Learning,2018
2. Learn to Schedule (LEASCH): A Deep Reinforcement Learning Approach for Radio Resource Scheduling in the 5G MAC Layer
3. The surprising effectiveness of MAPPO in cooperative, multi -agent games;yu;CoRR,2021
4. The Emergence of Wireless MAC Protocols with Multi-Agent Reinforcement Learning
5. Learning to communicate with deep multi-agent reinforcement learning;foerster;CoRR,2016
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