Darius Braziunas
Department of Computer Science
University of Toronto
Toronto, ON M5S 3H5
email: darius@cs.toronto.edu
Craig Boutilier
Department of Computer Science
University of Toronto
Toronto, ON M5S 3H5
email: cebly@cs.toronto.edu
Abstract
Structured utility models are essential for the effective
representation and elicitation of complex multiattribute
utility functions. Generalized additive independence
(GAI) models provide an attractive structural
model of user preferences, offering a balanced tradeoff
between simplicity and applicability. While representation
and inference with such models is reasonably
well understood, elicitation of the parameters of such
models has been studied less from a practical perspective.
We propose a procedure to elicit GAI model parameters
using only "local" utility queries rather than
"global" queries over full outcomes. Our local queries
take full advantage of GAI structure and provide a
sound framework for extending the elicitation procedure
to settings where the uncertainty over utility parameters
is represented probabilistically. We describe
experiments using a myopic value-of-information approach
to elicitation in a large GAI model.
To appear, UAI-05
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