Preferences are ubiquitous in everyday decision making.
They should therefore be an essential ingredient in every reasoning tool.
We will start by presenting the main approaches to model and reason with
preferences, such as soft constraints and CP-nets.
We will then analyze the complexity of solving problems with preferences,
identifying tractable tasks.
If there is time, we will briefly consider multi-agent settings, where several agents
express their preferences over common objects and the system should aggregate such
preferences into a single satisfying decision.
In this setting, we will show how notions and results from different fields, such
as social choice, matching, and multi-criteria decision making, can be helpful in AI scenarios.