Rational inattention with multiple attributes
提出一种新的学习成本度量，允许选项的不同属性有不同学习成本，该度量保持了香农经典度量的易处理性，但产生更丰富的选择预测，并识别出对福利和反事实分析重要的新信息偏差，同时给出了最优行为的充要条件。
This paper studies a new measure for the cost of learning that allows the different attributes of the options faced by an agent to differ in their associated learning costs. The new measure maintains the tractability of Shannon's classic measure but produces richer choice predictions and identifies a new form of informational bias significant for welfare and counterfactual analysis that is conducted with the multinomial logit model. Necessary and sufficient conditions are provided for optimal agent behavior under the new measure for the cost of learning.