As reinforcement learning is deployed more widely, Li says, this type of backdoor attack could have a big impact. Li points out that reinforcement-learning algorithms are typically used to control ...

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

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 ...

Unlike supervised learning, reinforcement learning algorithms must observe, and that can take time, said UC Berkeley professor Ion Stoica at Transform.

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

Reinforcement-learning algorithms mesh well with most games, because they tweak their behavior in response to positive feedback—the score going up.