Deep reinforcement learning leverages the learning capacity of deep neural networks to tackle problems that were too complex for classic RL techniques.

The deep learning pioneers believe that better neural network architectures will eventually lead to all aspects of human and animal intelligence, including symbol manipulation, reasoning, causal ...

Article reviewed by Grace Lindsay, PhD from New York University. Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain ...

Born in the 1950s, the concept of an artificial neural network has progressed considerably. Today, known as “deep learning”, its uses have expanded to many areas, including finance.

Reinforcement learning is a subset of machine learning. It enables an agent to learn through the consequences of actions in a specific environment.

Both deep learning and reinforcement learning are machine learning functions, which in turn are part of a wider set of artificial intelligence tools. What makes deep learning and reinforcement ...

Neural networks have revolutionized artificial intelligence. Here’s a look at the advantages, science, architecture behind them.