Active Queue-Management Policies for Undersea Networking via Deep Reinforcement Learning-Reference-Cited by-同舟云学术

Active Queue-Management Policies for Undersea Networking via Deep Reinforcement Learning

Published:2021-09-20 Issue: Volume: Page:
ISSN:
Container-title:OCEANS 2021: San Diego – Porto
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Author:

Forero Pedro A.¹,Zhang P.¹,Radosevic D.¹

Affiliation:

1. Naval Information Warfare Center Pacific,San Diego,CA,USA,92152

Funder

Naval Information Warfare Center Pacific

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9705657/9705658/09706025.pdf?arnumber=9706025

Reference17 articles.

1. Applications of Deep Reinforcement Learning in Communications and Networking: A Survey

2. Asynchronous methods for deep reinforcement learning;mnih;Proc of The 33rd International Conference on Machine Learning ser Proc of Machine Learning Research,2016

3. Controlling Queue Delay

4. Stable baselines3;hill,2019

5. Proximal policy optimization algorithms;schulman,2017

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