PDDQN-HHVBF Routing Protocol Based on Empirical Priority DDQN to Improve HHVBF
Reinforcement learning (RL) has been successfully applied to underwater routing protocols due to its powerful ability of distributed decision making. However, the traditional RL has slow convergence speed and low learning efficiency in underwater. Meanwhile, too many studies focus on using RL to fin...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-12-01
|
| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/11/23/4031 |