Probabilistic opinion pooling generalized. Part two: the premise-based approach
研究如何将多个人的概率函数汇总成一个集体概率函数，提出基于前提的方法，先汇总基本事件的概率再约束衍生事件，并在多种假设下得到线性或中性的意见汇总规则。
How can several individuals’ probability functions on a given $$\sigma $$ -algebra of events be aggregated into a collective probability function? Classic approaches to this problem usually require ‘event-wise independence’: the collective probability for each event should depend only on the individuals’ probabilities for that event. In practice, however, some events may be ‘basic’ and others ‘derivative’, so that it makes sense first to aggregate the probabilities for the former and then to let these constrain the probabilities for the latter. We formalize this idea by introducing a ‘premise-based’ approach to probabilistic opinion pooling, and show that, under a variety of assumptions, it leads to linear or neutral opinion pooling on the ‘premises’.