Multi-Agent Reinforcement Learning-Based Fairness-Aware Scheduling for Bursty Traffic
Author:
Affiliation:
1. School of Science and Engineering, The Chinese University of Hong Kong,Shenzhen,China,518172
Funder
National Key Research and Development Program of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9685019/9685006/09685661.pdf?arnumber=9685661
Reference8 articles.
1. Towards 5G: A Reinforcement Learning-Based Scheduling Solution for Data Traffic Management
2. A comparison of reinforcement learning algorithms in fairness-oriented ofdma schedulers;comsa;Information,2019
3. A Novel Scheduling Algorithm to Improve Average User Perceived Throughput for LTE Systems
4. Buffer-aware Wireless Scheduling based on Deep Reinforcement Learning
5. QMIX: Monotonic value function factorisation for deep multi-agent reinforcement learning;rashid;ArXiv Preprint,2018
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