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ICML
2009
IEEE

Online feature elicitation in interactive optimization

11 years 11 months ago
Online feature elicitation in interactive optimization
Most models of utility elicitation in decision support and interactive optimization assume a predefined set of "catalog" features over which user preferences are expressed. However, users may differ in the features over which they are most comfortable expressing their preferences. In this work we consider the problem of feature elicitation: a user's utility function is expressed using features whose definitions (in terms of "catalog" features) are unknown. We cast this as a problem of concept learning, but whose goal is to identify only enough about the concept to enable a good decision to be recommended. We describe computational procedures for identifying optimal alternatives w.r.t. minimax regret in the presence of concept uncertainty; and describe several heuristic query strategies that focus on reduction of relevant concept uncertainty.
Craig Boutilier, Kevin Regan, Paolo Viappiani
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2009
Where ICML
Authors Craig Boutilier, Kevin Regan, Paolo Viappiani
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