Abstract
Effective optimization is essential for interactive
systems to provide a satisfactory user experience.
However, it is often challenging to find an objective to optimize for. Generally, such objectives are
manually crafted and rarely capture complex user
needs in an accurate manner. We propose to infer
the objective directly from observed user interactions. These inferences can be made regardless of
prior knowledge and across different types of user
behavior. It is promising if we model the objectives
directly from the user interactions which we use to
optimize interactive systems, which will improve
user experience and dynamically reacts to user actions