This tutorial, addressed to researchers and practitioners in the area of recommendation systems, reviews the foundations of decision and utility theory, focusing on methods for representing, learning and reasoning with preferences. Recent advances on handling preferences will also be discussed, with a focus on preference learning, preference aggregation and preferences in argumentation. Finally, we will show how these techniques can be used in a practice in recommender systems.