Quantum computing will not deliver truly useful business results overnight, but the pace of progress is no longer linear; ...

This paper presents the hierarchical Q-learning path planning (HQPP) architecture for solving the cooperative tracking control problem of multi-agent systems (MASs) with lumped uncertainties in an ...

The strategic advantage of QML continues to expand its presence in industries that deal with complex, high-dimensional data.

The deadline is closing in, compiler errors keep flashing across your screen, and the fear of lost GPA points feels like a ...

Implementing Reinforcement Learning, namely Q-learning and Sarsa algorithms, for global path planning of mobile robot in unknown environment with obstacles. Comparison analysis of Q-learning and Sa ...

Q-learning is a model-free, value-based, off-policy algorithm for reinforcement learning that will find the best series of actions based on the current state. The “Q” stands for quality.

We first applied an unsupervised learning algorithm using a variational autoencoder with K‐means clustering to cluster atrial fibrillation patients into 8 distinct phenotypes. We then fit a Q‐learning ...