Old Evidence and New Explanation

科学理论是用来解释一系列特定现象的。然而，从直觉上讲，如果一种新理论不仅能解释它专门要解决的现象，而且还能从我们已经接受的东西中得出结论，我们就会倾向于增加对它的信任。然而，在贝叶斯概率论中，在证实科学理论的主流传统中，旧的证据并不会增加新理论成立的可能性。这个所谓的“旧证据/新解释”问题应该如何解决？理查德·杰弗里提出了一个解决方案。瓦格纳教授正在扩展杰弗里的原理，并在此过程中产生了两种不同的修正方法来概括这个问题。PI将调查这一现象的数学和哲学方面，这既是因为对旧证据/新解释问题的概括的内在兴趣，也是为了澄清杰弗里对这一问题经典版本的解决方案的本质。

Theories are created in science to explain a certain set of phenomena. Intuitively, however, we tend to increase our belief in a new theory if it not only explains the phenomena that it was specifically created to address but then is found to follow from something we had already accepted. Yet in Bayesian Probability Theory, the dominant tradition concerning the confirmation of scientific theories, old evidence does not increase the probability of new theories. How should this so-called `old evidence/new explanation` issue be resolved? Richard Jeffrey came up with one solution. Professor Wagner is extending Jeffrey's principles and, in process, gives rise to two different revision methods for generalization of this problem. The PI will investigate both the mathematical and the philosophical aspects of this phenomenon, both because of the intrinsic interest of generalizations of the old evidence/new explanation problem and in order to clarify the essence of Jeffrey's solution to the classical version of this problem.