Deep reinforcement learning has helped solve very complicated challenges and will continue to be an ... a deep neural network can learn an optimal policy without going through all the possible ...

As AI researchers venture into the areas of Meta-Learning, attempting to give AI learning capabilities, in conjunction with deep learning, reinforcement learning will play a crucial role.

In recent years, deep-learning techniques using neural networks have been used in conjunction with reinforcement learning, resulting in a novel approach called “deep-reinforcement learning ...

Deep learning is often compared to the brains of humans and animals.However, the past years have proven that artificial neural networks, the main component used in deep learning models, lack the ...

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.

Researchers from the University of Tokyo in collaboration with Aisin Corporation have demonstrated that universal scaling ...

The 2012 breakthrough—the deep learning revolution—was the discovery that we can get dramatically better performance out of neural networks with not just a few layers but with many.

Neural networks are now applied across the spectrum of AI applications while deep learning is reserved for more specialized or advanced AI use cases.