Policy Learning with Human Teachers: Using directive feedback in a Gaussian framework

A prevalent approach for learning a control policy in the model-free domain is by engaging Reinforcement Learning (RL). A well known disadvantage of RL is the necessity for extensive amounts of data for a suitable control policy. For systems that concern physical application, acquiring this vast amount of data might take an extraordinary amount...