One of the most interesting AI trends is the convergence of reinforcement learning with supervised and unsupervised learning in more advanced applications.

What is supervised learning? One last thing you need to know: machine (and deep) learning comes in three flavors: supervised, unsupervised, and reinforcement.

Reinforcement learning and simulation are essential to solving the constraints and novel challenges that take place in factories and supply chains.

An algorithm that learns through rewards may show how our brain does too By optimizing reinforcement-learning algorithms, DeepMind uncovered new details about how dopamine helps the brain learn.

A new research paper titled “Discovering faster matrix multiplication algorithms with reinforcement learning” was published by researchers at DeepMind. “Here we report a deep reinforcement learning ...

Their machine learning algorithms are now capable of training themselves, so to speak, thanks to the reinforcement learning methods of their OpenAI Baselines.

What is Reinforcement Learning? At the core of reinforcement learning is the concept that the optimal behavior or action is reinforced by a positive reward.

The paper elaborates on a technique for using knowledge graphs with machine learning; specifically, a branch of machine learning called reinforcement learning.