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Inferentialism, Bayesianism and Scientific Explanation

推理主义、贝叶斯主义和科学解释

基本信息

批准号：
278967060
负责人：
Professor Dr. Stephan Hartmann
金额：
--
依托单位：
Lehrstuhl für Logik und Sprachphilosophie
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2015
资助国家：
德国
起止时间：
2014-12-31 至 2018-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/278967060?language=en
关键词：
Inferentialism Bayesianism Scientific Explanation

项目摘要

Explanation constitutes a cornerstone of scientific rationality. But what is valid explanatory reasoning? And when is valid explanatory reasoning a guide to truth? Although these questions have generated much debate, no unanimously accepted answers have emerged. Our research program aims to break the deadlock in the debate between different philosophical theories of explanation and to develop a new account of explanatory reasoning. To do so, the proposed research program synthesizes approaches from philosophy of language (inferentialism) and formal epistemology (Bayesianism). First, we will appeal to inferentialism to justify the interpretation of explanations as arguments that facilitate the inference to the explanandum by providing reasons. Secondly, we will use Bayesianism to quantitatively reconstruct the dynamics of explanatory reasoning in probabilistic terms. Finally, we will investigate the possibility to systematically integrate the two approaches in order to vindicate the rationality of an explanatory pattern commonly used in scientific practice, viz. inference to the best explanation. Our results will be informed by an in depth analysis of two case studies: one from economics, viz. the explanation of the stylized facts of finance, and one from biology, viz. the explanation of biological functions, whose explanatory value is hard to account for by reference to traditional theories of scientific explanation. The combined use of inferentialism and Bayesianism and the application to the case studies will allow us to tackle the traditional task of interpreting scientific explanation from an innovative perspective, both normatively and scientifically informed.

解释构成了科学合理性的基石。但什么是有效的解释性推理呢？什么时候有效的解释性推理才是真理的指南呢？尽管这些问题引起了很多争论，但还没有出现一致接受的答案。我们的研究计划旨在打破不同哲学解释理论之间的争论僵局，并开发一种解释推理的新账户。为此，拟议的研究方案综合了语言哲学(推理主义)和形式认识论(贝叶斯主义)的方法。首先，我们将呼吁推理主义通过提供理由来证明将解释解释为便于对解释大纲进行推理的论点是合理的。其次，我们将使用贝叶斯理论以概率术语定量重建解释性推理的动力学。最后，我们将探讨系统地整合这两种方法的可能性，以证明科学实践中常用的解释模式的合理性。推论出最好的解释。我们的结果将通过对两个案例的深入分析而得出：一个来自经济学，即。对金融学的程式化事实的解释，以及对生物学的解释，即。对生物功能的解释，其解释价值很难用传统的科学解释理论来解释。推理主义和贝叶斯主义的结合以及在案例研究中的应用将使我们能够解决从创新的角度解释科学解释的传统任务，既有规范的，也有科学的。