Reinforcement Learning
Reinforcement Learning So far we have seen two major paradigms of machine learning supervised and unsupervised learning. Supervised learning involves learning with labeled data, where as unsupervised methods learns from unlabeled data and seeks to find the hidden structures in the data. Reinforcement learning (RL) is neither supervised nor unsupervised, but addresses the learning problem by maximizing a reward signal. Unlike the other two methods RL is a continuous trade off between exploration and exploitation . RL c ould also be called action-based learning . Figure-1: A short history Reinforcement learning methods has its roots in two entirely independent areas. One that is inspired by natural learning mechanisms, to learn by trial and error and originated in psychology of animal learning and training. It was used by Russian physiologist Ivan Petrovich Pavlov in the 1890s to train his dogs. Animals adjust their a...