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

Reinforcement learning explained Reinforcement learning is a teaching algorithm. A subject operates in an environment with a current state and actions that it can perform.

Reinforcement-learning algorithms 1,2 are inspired by our understanding of decision making in humans and other animals in which learning is supervised through the use of reward signals in response ...

Reinforcement learning (RL) is a branch of machine learning that addresses problems where there is no explicit training data. Q-learning is an algorithm that can be used to solve some types of RL ...

Reinforcement learning (RL) is a powerful type of AI technology that can learn strategies to optimally control large, complex systems.

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.

By contrast, the AlphaGo Zero program recently achieved superhuman performance in the game of Go by reinforcement learning from self-play. In this paper, we generalize this approach into a single ...