We consider the challenge of preference elicitation in systems that help users discover the most desirable item(s) within a given database. Past work on preference elicitation foc...
Preference elicitation is a serious bottleneck in many decision support applications and agent specification tasks. CP-nets were designed to make the preference elicitation proces...
Intelligent agents often need to assess user utility functions in order to make decisions on their behalf, or predict their behavior. When uncertainty exists over the precise natu...
Any automated decision support software must tailor its actions or recommendations to the preferences of different users. Thus it requires some representation of user preferences ...
Research on preference elicitation and reasoning typically focuses on preferences over single objects of interest. However, in a number of applications the "outcomes" of...
Ronen I. Brafman, Carmel Domshlak, Solomon Eyal Sh...
We consider how to combine the preferences of multiple agents despite the presence of incompleteness and incomparability in their preference orderings. An agent’s preference orde...
Maria Silvia Pini, Francesca Rossi, Kristen Brent ...
The enormous number of questions needed to acquire a full preference model when the size of the outcome space is large forces us to work with partial models that approximate the u...
Complexity theory is a useful tool to study computational issues surrounding the elicitation of preferences, as well as the strategic manipulation of elections aggregating togethe...
The ability for an agent to reason under uncertainty is crucial for many planning applications, since an agent rarely has access to complete, error-free information about its envi...
Abstract. Very often a planning problem can be formulated as a ranking problem: i.e. to find an order relation over a set of alternatives. The ranking of a finite set of alternat...