Reinforcement Learning: A Brief Overview

Abstract

Learning techniques can be usefully grouped by the type of feedback that is available to the learner. A commonly drawn distinction is that between supervised and unsupervised techniques. In supervised learning a teacher gives the learner the correct answers for each input example. The task of the learner is to infer a function which returns the correct answers for these exemplars while generalising well to new data. In unsupervised learning the learner’s task is to capture and summarise regularities present in the input examples. Reinforcement learning (RL) problems fall somewhere between these two by giving not the correct response, but an indication of how good an response is. The learner’s task in this framework is to learn to produce repsonses that maximise goodness.