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.

There are many different types of reinforcement learning algorithms, but two main categories are “model-based” and “model-free” RL. They are both inspired by our understanding of learning ...

People store large quantities of data in their electronic devices and transfer some of this data to others, whether for professional or personal reasons. Data compression methods are thus of the ...

The first available use case for BeeKeeper, Mount Sinai and Morehouse is for chronic heart failure (CHF). AI model developers ...

Better data annotation—more accurate, detailed or contextually rich—can drastically improve an AI system’s performance, ...

A new analysis suggests artificial intelligence algorithms are able to accurately assess lesion severity in patients with ...