Multi-armed Bandits with Covariates: Theory and Applications

Abstract
Multi-armed bandits with covariates, also called "contextual bandits" in machine learning, have become an active area of research in recent years because of their applications to the development of personalized strategies in translational medicine and in recommender systems for web-based marketing and electronic business. After a brief review of classical (context-free) bandit theory, we describe a corresponding theory for contextual bandits and illustrate its applications to personalized strategies.