Training a Machine Learning Algorithm with Python Using the Iris Flowers Dataset For this example, we will be using the Jupyter Notebook to train a machine learning algorithm with the classic Iris ...

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 uses rewards and penalties to teach computers how to play games and robots how to perform tasks independently ...

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 ...

The framework is detailed in the survey paper " Survey of recent multi-agent reinforcement learning algorithms utilizing centralized training," which is featured in the SPIE Digital Library.

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 ...