A Study of Conditionalization

在概率论中，人们必须关心的是 在提出新的条件之前进行思考（即“先验”） 或先验概率）。 理查德·杰弗里介绍了一个 更新a的普通条件化的推广 根据新的证据， 重新评估某个划分的成员的概率 一个样本空间。 瓦格纳博士正在研究一个概括 杰弗里的条件化，其中新的证据 一种较低类型的先前的可能修订 Dempster首先研究了概率， Shafer描述并命名为置信函数。 作为这项研究的一个预期的哲学结果，博士。 瓦格纳希望展示杰弗里式的优越性 更新方法，而不是机械更新方法， 这是一个简单的假设，也就是说， Jeffrey规则的结果与Maxent的结果一致，因为 这不是自然推广的情况， 杰弗里的规则，他建议）。 另一个目标是 明确区分条件化和 对称组合技术，如Dempster规则。 最后，他希望表明，邓普斯特的建设， 较低的概率提供了完全令人满意的响应， 卡尔纳普要求理性地构建新的 Jeffrey分区的概率

Within probability theory, one must be concerned with what one thinks before new conditions are presented (i.e. the "priors" or prior probabilities). Richard Jeffrey presented a generalization of ordinary conditionalization to update a "prior" in the light of new evidence that dictates a reassessment of the probabilities of members of some partition of a sample space. Dr. Wagner is studying a generalization of Jeffrey's conditionalization in which new evidence bounds the possible revisions of a prior below by a type of lower probability first studied by Dempster, and later abstractly characterized and termed a belief function by Shafer. As an anticipated philosophical consequence of this study, Dr. Wagner hopes to show the superiority of Jeffrey-type approaches to updating over mechanical updating methods such as maxent (and to establish that it is simple a fluke that the results of Jeffrey's rule coincide with those of maxent,since this is not the case for the natural generalization of Jeffrey's rule which he proposes). An additional aim is to establish a clear distinction between conditionalization and symmetric combination techniques such as Dempster's rule. Finally, he hopes to show that Dempster's construction of lower probabilities provides a fully satisfactory response to Carnap's demand for a reasoned construction of the new probabilities on a Jeffrey partition.