  Deep reinforcement learning is the combination of reinforcement learning (RL)
and deep learning. This field of research has been able to solve a wide range
of complex decision-making tasks that were previously out of reach for a
machine. Thus, deep RL opens up many new applications in domains such as
healthcare, robotics, smart grids, finance, and many more. This manuscript
provides an introduction to deep reinforcement learning models, algorithms and
techniques. Particular focus is on the aspects related to generalization and
how deep RL can be used for practical applications. We assume the reader is
familiar with basic machine learning concepts.
