9 awesome real world applications of Reinforcement Learning

Reinforcement Learning is a framework for sequential decision making. It differs from the usual supervised setting as there are no labels present. In this framework an'agent' interacts with an'environment' to gain experience from which the agent learns to perform the most optimal action which maximises its rewards. Reinforcement Learning has had major advances in the last few years and is being applied to real world problems. The pace of adoption has definitely been slower than other ML approaches as RL has its own challenges.