Name
Title | ||
|---|---|---|
Combining Long-Short Term Memory and Reinforcement Learning for Improved Autonomous Network Operation |
Abstract | ||
|---|---|---|
A combined LSTM and RL approach is proposed for dynamic connection capacity allocation. The LSTM predictor anticipates periodical long-term sharp traffic changes and extends short-term RL knowledge. Numerical results show remarkable performance. (C) 2021 The Authors |
Year | Venue | DocType |
|---|---|---|
2021 | 2021 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXPOSITION (OFC) | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fatemehsadat Tabatabaeimehr | 1 | 0 | 1.01 |
| Sima Barzegar | 2 | 3 | 2.82 |
| Marc Ruiz | 3 | 0 | 0.34 |
| Luis Velasco | 4 | 0 | 0.34 |