A Constraint-Based Approach to Preference Elicitation and Decision Making

Craig Boutilier, Ronen I. Brafman, Christopher Geib and David Poole
Department of Computer Science
University of British Columbia
Vancouver, BC, CANADA, V6T 1Z4
email: cebly,brafman,geib,poole@cs.ubc.ca

We investigate the solution of constraint-based configuration problems in which the preference function over outcomes is unknown or incompletely specified. The aim is to configure a system, such as a personal computer, so that it will be optimal for a given user. The goal of this project is to develop algorithms that generate the most preferred feasible configuration by posing preference queries to the user. In order to minimize the number and the complexity of preference queries posed to the user, the algorithm reasons about the user's preferences while taking into account constraints over the set of feasible configurations. We assume that the user can structure their preferences in a particular way that, while natural in many settings, can be exploited during the optimization process. We also address in a preliminary fashion the trade-offs between computational effort in the solution of a problem and the degree of interaction with the user.

Appeared, AAAI Spring Symposium on Qualitative Decision Theory, March 1997

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