Value Alignment via Tractable Preference Distance

Abstract

Preferences are ubiquitous in everyday life we use our own subjective preferences whenever we want to make a decision to choose our most preferred alternative. Hence, the study of preferences in computer science and AI has been very active for a number of years with important theoretical and practical results as well as libraries and datasets . In many scenarios including multiagent systems and recommender systems, user preference play a key role in driving the decisions the system makes. Thus it is important to have preference modeling frameworks that allow for expressive and compact representations, effective elicitation techniques, and effcient reasoning and aggregation