Preferences in Interactive Systems: Technical Challenges and Case Studies

Interactive artificial intelligence systems employ preferences in both their reasoning and their interaction with the user. This survey considers preference handling in applications such as recommender systems, personal assistant agents, and personalized user interfaces. We survey the major questions and approaches, present illustrative examples, and give an outlook on potential benefits and challenges. A popular example is Netflix, which gives customized movie recommendations to each user, using past movie ratings of the user and his or her friends. Netflix and other preference-aware interactive systems share the common aim of aiding the user in carrying out tasks--from finding a product to editing a document--by eliciting preferences from the user, inferring a preference model, and using the model to decide when and how to take action.