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Efficiently Eliciting Preferences from a Group of Users

机译:有效地从一组用户引出偏好

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Learning about users' preferences allows agents to make intelligent decisions on behalf of users. When we are eliciting preferences from a group of users, we can use the preferences of the users we have already processed to increase the efficiency of the elicitation process for the remaining users. However, current methods either require strong prior knowledge about the users' preferences or can be overly cautious and inefficient. Our method, based on standard techniques from non-parametric statistics, allows the controller to choose a balance between prior knowledge and efficiency. This balance is investigated through experimental results.
机译:学习用户的首选项允许代理代表用户制作智能决策。当我们引起一组用户的偏好时,我们可以使用我们已经处理的用户的偏好来提高剩余用户的诱导过程的效率。但是,目前的方法要么需要强烈的关于用户偏好的先验知识,也需要过度谨慎且效率低下。我们的方法基于来自非参数统计的标准技术,允许控制器在先验知识和效率之间选择平衡。通过实验结果调查这种平衡。

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