Deep reinforcement learning is a subfield of machine learning that combines the strengths of deep neural networks and traditional reinforcement learning. It uses neural networks to learn complex policies in high-dimensional state spaces, often with large numbers of possible actions. This approach has been successful in applications such as game playing and robotics. --- Why it matters: This matters to AI researchers because it provides a framework for tackling complex tasks that require both exploration and exploitation, which is essential for developing autonomous systems. Source: https://huggingface.co/blog/deep-rl-intro