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Adaptive cache policy optimization through deep reinforcement learning in dynamic cellular networks

Ashvin Srinivasan Mohsen Amidzadeh Junshan Zhang Olav Tirkkonen

智能与融合网络（英文）2024，Vol.5Issue(2)：81-99,19.

智能与融合网络（英文）2024，Vol.5Issue(2)：81-99,19.DOI:10.23919/ICN.2024.0007

Adaptive cache policy optimization through deep reinforcement learning in dynamic cellular networks

Ashvin Srinivasan ¹Mohsen Amidzadeh ¹Junshan Zhang ²Olav Tirkkonen¹

作者信息

1. Department of Information and Communications Engineering,Aalto University,Espoo 02150,Finland
2. Department of Electrical and Computer Engineering,University of California,Davis,CA 95616,USA
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摘要

关键词

wireless caching/deep reinforcement learning/advantageous actor critic/long short term memory/non-stationary Partial Observable Markov Decision Process(POMDP)

Key words

wireless caching/deep reinforcement learning/advantageous actor critic/long short term memory/non-stationary Partial Observable Markov Decision Process(POMDP)

引用本文复制引用

Ashvin Srinivasan,Mohsen Amidzadeh,Junshan Zhang,Olav Tirkkonen..Adaptive cache policy optimization through deep reinforcement learning in dynamic cellular networks[J].智能与融合网络（英文）,2024,5(2):81-99,19.

基金项目

This work was supported in part by the Academy of Finland(No.345109). （No.345109）

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