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 ...
IEEE

Q-Learning-Based Control for Discrete-Time Switched Affine Systems and Its Application to DC–DC Converter

Abstract: In this paper, a new data-based Q-learning algorithm is proposed to address the optimal control issue for a class of discrete-time switched affine systems (SASs). The algorithm shifts the ...
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 ...
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 ...