Reinforcement-Learning-based Network Design and Control with Stepwise Reward Variation and Link-Adjacency Embedding

被引:0
作者
Cruzado, Kenji [1 ]
Shiraki, Ryuta [1 ]
Mori, Yojiro [1 ]
Tanaka, Takafumi [2 ]
Higashimori, Katsuaki [2 ]
Inuzuka, Fumikazu [2 ]
Ohara, Takuya [2 ]
Hasegawa, Hiroshi [1 ]
机构
[1] Nagoya University, Furo-cho, Chikusa, Aichi, Nagoya,464-8603, Japan
[2] Ntt Corporation, 1-1 Hikari-no-oka, , Kanagawa, Yokosuka,239-0847, Japan
来源
2022 European Conference on Optical Communication, ECOC 2022 | 2022年
关键词
Compilation and indexing terms; Copyright 2024 Elsevier Inc;
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摘要
Capacity enhancement - Congestion-aware - Design and control - Embeddings - First fit - Input parameter - Link utilization - Network design - Network-control - Reinforcement learnings
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