Electronics360

Wind turbine control systems: From PID to reinforcement learning

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...
IEEE

Optimizing Successive Over-relaxation Q-learning with Deterministic Perturbation Gradient Search

Abstract: Successive Over-Relaxation Q-learning (SOR-QL) has been proposed recently as an alternative to the widely popular Q-learning algorithm as it is seen to provide better performance where ...
Frontiers

A novel reinforcement learning framework-based path planning algorithm for unmanned surface vehicle

Unmanned surface vehicles (USVs) nowadays have been widely used in ocean observation missions, helping researchers to monitor climate change, collect environmental data, and observe marine ecosystem ...
eLife

Q-learning with temporal memory to navigate turbulence

This important study uses reinforcement learning to study how turbulent odor stimuli should be processed to yield successful navigation. The authors find that there is an optimal memory length over ...
IEEE

Evolution-Guided Q-Learning With Dual Swarm Intelligence for Model-Free Optimal Control

Abstract: In this article, a novel accelerated evolution-guided Q-learning (EGQL) algorithm is introduced to address optimal control problems for unknown nonlinear systems. A novel adaptive ...
Frontiers

Deep reinforcement learning and robust SLAM based robotic control algorithm for self-driving path optimization

A reward shaping deep deterministic policy gradient (RS-DDPG) and simultaneous localization and mapping (SLAM) path tracking algorithm is proposed to address the issues of low accuracy and poor ...