Inter-Cell Slicing Resource Partitioning via Coordinated Multi-Agent Deep Reinforcement Learning
Author:
Affiliation:
1. Nokia Bell Labs,Stuttgart,Germany,Germany
2. University of Nebraska-Lincoln,School of Computing,United States
3. Nokia Software,Bellevue,United States
4. Technical University of Munich,Dept. of Informatics,Germany
Funder
Ministry of Education
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9837954/9838246/09838518.pdf?arnumber=9838518
Reference19 articles.
1. A Deep Reinforcement Learning Framework for Spectrum Management in Dynamic Spectrum Access
2. Deep Reinforcement Learning Based Resource Management for Multi-Access Edge Computing in Vehicular Networks
3. Constrained reinforcement learning has zero duality gap;paternain,2019
4. Safe exploration in continuous action spaces;dalal,2018
5. Learning to communicate with deep multi-agent reinforcement learning;foerster,2016
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