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.

本文研究了使用结构化效用模型进行复杂多属性效用函数的有效表示和引导。通过使用广义加性独立模型作为用户偏好的结构模型，我们提出了一种仅使用“局部”效用查询而不是全局查询来引导这些模型参数的方法。同时，我们采用了简单易行的策略，将此方法扩展到将效用参数的不确定性概率表示。最后，我们通过一种我的信息价值方法来实验验证该方法。

GAI模型中的本地效用引出