Deep Reinforcement Learning Based Probabilistic Cognitive Routing: An Empirical Study with OMNeT++ and P4-Reference-Cited by-同舟云学术

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Deep Reinforcement Learning Based Probabilistic Cognitive Routing: An Empirical Study with OMNeT++ and P4

Published:2023-10-30 Issue: Volume: Page:
ISSN:
Container-title:2023 19th International Conference on Network and Service Management (CNSM)
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Author:

Wang Yixing¹,Xiao Yang¹,Song Yuqian¹,Zhou Jingli¹,Liu Jun¹

Affiliation:

1. School of Artificial Intelligence, Beijing University of Posts and Telecommunications,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10327686/10327788/10327868.pdf?arnumber=10327868

Reference22 articles.

1. Fast Traffic Engineering by Gradient Descent with Learned Differentiable Routing

2. DOTE: Rethinking (predictive) WAN traffic engineering;perry;20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23),0

3. RL-Routing: An SDN Routing Algorithm Based on Deep Reinforcement Learning

4. Leveraging Deep Reinforcement Learning for Traffic Engineering: A Survey

5. Toward Packet Routing With Fully Distributed Multiagent Deep Reinforcement Learning

Cited by 1 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 Comprehensive Review of Recent Developments in VANET for Traffic, Safety & Remote Monitoring Applications;Journal of Network and Systems Management;2024-08-08

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