Multi Pseudo Q-Learning-Based Deterministic Policy Gradient for Tracking Control of Autonomous Underwater Vehicles.
Wenjie ShiShiji SongCheng WuC. L. Philip ChenPublished in: IEEE Trans. Neural Networks Learn. Syst. (2019)
Keyphrases
- tracking control
- policy gradient
- reinforcement learning
- function approximation
- reinforcement learning algorithms
- nonlinear systems
- control law
- state action
- cooperative
- multi agent
- autonomous underwater vehicles
- reinforcement learning methods
- action selection
- adaptive control
- learning rate
- fuzzy controller
- dynamic programming
- optimal control
- state space
- model free
- temporal difference
- control strategy