Reinforcement Learning, a type of Machine learning algorithm, which is based on the feedback loop where an agent and environment is set up.
The way it works is the agent learns to behave in an environment, by performing certain actions and observing the rewards and results which it gets from those actions. Hence This technique is behavior-driven and is based on the reinforcements learned via trial-and-error. Example: to learn how to ride a bicycle. This method can be used to optimize the operational productivity of systems including supply chain logistics, manufacturing and robotics.
