On Design and Implementation of Reinforcement Learning Based Cognitive Routing for Autonomous Networks

Author:

Xiao Yang1ORCID,Li Jianxue1ORCID,Wu Jiawei1ORCID,Liu Jun1ORCID

Affiliation:

1. Intelligent Perception and Computing Research Center, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China

Funder

BUPT Excellent Ph.D. Students Foundation

Ministry of Education (MoE)-China Mobile Communications Group Co.,Ltd. (CMCC) Artificial Intelligence Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation

Reference16 articles.

1. Continuous control with deep reinforcement learning;lillicrap;arXiv 1509 02971,2015

2. RLlib: Abstractions for distributed reinforcement learning;liang;Proc 35th Int Conf Mach Learn (ICML),2018

3. Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor;haarnoja;Proc 35th Int Conf Mach Learn (ICML),2018

4. Proximal policy optimization algorithms;schulman;arXiv 1707 06347,2017

5. Knowledge-Defined Networking

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3. Deep Reinforcement Learning Based Probabilistic Cognitive Routing: An Empirical Study with OMNeT++ and P4;2023 19th International Conference on Network and Service Management (CNSM);2023-10-30

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