Machine learning is a powerful tool that can be used to solve a variety of problems. However, it is important to note that machine learning algorithms are only as good as the data they are trained on.

So, reinforcement learning algorithms have all the same philosophical limitations as regular machine learning algorithms. These are already well-known by machine learning scientists.

Indeed, the first application in which reinforcement learning gained notoriety was when AlphaGo, a machine learning algorithm, won against one of the world’s best human players in the game Go.

Most machine learning algorithms are shouting names in the street. They perform perceptive tasks that a person can do in under a second. But another kind of AI — deep reinforcement learning ...

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing ...

By contrast, this newly proposed safe reinforcement learning algorithm only assumes access to a sparse indicator for catastrophic failure. And it trains a conservative safety critic that ...

A machine learning approach leverages nuclear microreactor symmetry to reduce training time when modeling power output ...

Machine automation increasingly relies on machine learning. For example, self-driving car technology is deeply indebted to machine learning algorithms for the ability to detect objects on the road ...

algorithms artificial intelligence computer science deep learning explainers machine learning natural language processing neural networks reinforcement learning All topics By now, many people think ...