A core topic in Machine Learning is that of sequential decision-making. This is the task of deciding, from experience, the sequence of actions to perform in an uncertain environment in order to achieve some goals. Sequential decision-making tasks cover a wide range of possible applications with the potential to impact many domains, such as finance (intelligent algorithmic trading), robotics, healthcare, self-driving cars, and many more. Inspired by behavioural psychology, Deep Reinforcement Learning (RL) proposes a formal framework to this problem. Deep RL has also started to receive a lot of attention since the January of 2016, when a team of researchers from Google built a Deep RL based AI that beat the reigning world champion of the board game Go. So what is Deep RL? Let’s explore!