REINFORCEMENT LEARNING AND ITS APPLICATIONS

Reinforcement learning comes under the field of machine learning which one of the dominating research fields these days. It is a semi-supervised method of learning in which actions are taken to maximize the reward in a particular direction. It is a sequential method in which the next output depends on the previous input and hence a computer system intelligently decides on the basis of the experiences gained. Authors have discussed the basic methodology of reinforcement learning and the challenges faced by it. Another topic discussed herein is the applications of reinforcement learning. Some of the applications of reinforcement learning are Resources management in computer clusters, Traffic light control, Robotics, Web system configuration, Chemistry, Personalized recommendations and deep learning. Results have proved that reinforcement learning is a better method of machine learning when an automatic system need to be created. This technique helps in smart and real time learning of a system to perform according to the present situation in an experiment