What is deep reinforcement learning?

Deep reinforcement learning is the combination of deep learning and reinforcement learning.

  • Deep learning is a collection of techniques using artificial neural networks that mimic the structure of the human brain. With deep learning, computers can recognize complex patterns in large amounts of data, extract insights, or make predictions, without being explicitly programmed to do so. The training can consist of supervised learning, unsupervised learning, or reinforcement learning.
  • Reinforcement learning (RL) is a learning mode in which a computer interacts with an environment, receives feedback and, based on that, adjusts its decision-making strategy.
  • Deep reinforcement learning is a specialized form of RL that utilizes deep neural networks to solve more complex problems. In deep reinforcement learning, we combine the pattern recognition strengths of deep learning and neural networks with the feedback-based learning of RL.