Old Evidence and New Explanation

理论是在科学中创造的，用来解释一组特定的现象。然而，直觉上，如果一个新的理论不仅解释了它专门为解决的现象而创造出来的现象，而且后来发现它是从我们已经接受的东西发展而来的，那么我们倾向于增加我们对新理论的信念。然而，在贝叶斯概率论中，关于科学理论确认的主导传统，旧的证据并不增加新理论的概率。这个所谓的‘旧证据/新解释’问题应该如何解决？理查德·杰弗里想出了一个解决方案。瓦格纳教授正在推广杰弗里的原理，并在此过程中提出了两种不同的修正方法来推广这一问题。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的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.