文章摘要
贝叶斯主义科学方法论的解题功能及困境
The Solving Function and the Plight of the Bayesianism Methodology
  
DOI:
中文关键词: 贝叶斯主义  功能  困境  认知转向  贝叶斯网络
英文关键词: Bayesianism  function  plight  the cognitive turn  Bayesian network
基金项目:
作者单位
程和祥 南京大学 哲学系江苏 南京 210023 
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中文摘要:
      贝叶斯主义兴起于20世纪30年代,在90年代得到复兴,目前已成为科学方法论的重要研究纲领。在科学推理领域,贝叶斯主义具有如下优势:能够将传统科学方法论中的重要直觉形式化;避开传统科学方法论中的困难;解决传统科学方法论中的“未解之谜”。但它也面临旧证据问题、逻辑全知问题和简单性问题以及可列可加性问题等困境。当前贝叶斯主义的研究活力主要表现在两个方面:认知科学中的贝叶斯推理和人工智能领域中的贝叶斯网络研究。
英文摘要:
      The Bayesianism, which arose in the 1930s on the basis of the Bayes theorem and revived in the 1990s, has become the important research program and the hotspot of scientific methodology. In the field of scientific reasoning, the Bayesianism has the following advantages, i.e. formalizing the important intuitions of the traditional scientific methodology, avoiding the difficulties in the traditional scientific methodology, and resolving the “mysteries” of the traditional scientific methodology. But it also has some dilemmas, such as old evidence, logical omniscience, simplicity, countable additivity, and so on. Currently, the researches on the Bayesianism study has m mainly anifested in two aspects, that is the Bayesian inference in cognitive science, and the Bayesian network in artificial intelligence.
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