Radical Probabilism and Bayesian Conditioning*
Radical Probabilism and Bayesian Conditioning*
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激进概率论和贝叶斯条件*
DOI：
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发表时间：
2005
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通讯作者：
Richard Bradley
中科院分区：
文献类型：
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作者：
Richard Bradley
理查德·杰弗里（Richard Jeffrey）支持贝叶斯思想的一种反基础主义变体，他称之为“激进概率论”。激进概率论否认存在一个理想的，公正的起点，我们试图了解世界和经典贝叶斯主义的教条，唯一合理的改变信仰是一个基于学习的基础上。或然判断是基本的、不可约的。当与环境的相互作用产生了对某些命题的新的信念的确定性，但使一个人的条件信念不变（“刚性”条件）时，贝叶斯条件是合适的。虽然理查德·杰弗里否认了这一条件的普遍适用性，但他对概率思维的主要贡献之一是一种信念更新的形式-现在通常称为“杰弗里条件反射”或“概率运动学”-这在刚性得到满足的情况下是合适的，但是，这种相互作用使人们重新评估自己对可能性空间的某个分区的概率判断，而不赋予任何确定性。特殊元素。杰弗里条件反射最常见的情况是接收不确定的证据：部分感知或记忆的事物。但它也有助于阐明由一个人的条件信念程度的变化所引起的信念更新，这是一种被经典贝叶斯主义所忽视的信念变化。我认为，条件信念的这种变化也可以是基本的（在这个意义上说，作为对事实信息的条件作用的结果，这种变化是不可分析的），并为条件信念的一种特殊变化提供了一个运动学模型。两者都适用于偏好的变化。最后，我认为，刚性可以失败时，信念的变化，有条件的信念变化的推理理由（反之亦然）。这些失败表明，条件反射方法被正确地认为不是有效的推理规则，而是“判断的艺术”中的工具。
Richard Jeffrey espoused an antifoundationalist variant of Bayesian thinking that he termed ‘Radical Probabilism’. Radical Probabilism denies both the existence of an ideal, unbiased starting point for our attempts to learn about the world and the dogma of classical Bayesianism that the only justified change of belief is one based on the learning of certainties. Probabilistic judgment is basic and irreducible. Bayesian conditioning is appropriate when interaction with the environment yields new certainty of belief in some proposition but leaves one’s conditional beliefs untouched (the ‘Rigidity’ condition). Although Richard Jeffrey denied the general applicability of this condition, one of his main contributions to probabilistic thinking is a form of belief updating—now typically called ‘Jeffrey conditioning’ or ‘probability kinematics’—that is appropriate in circumstances in which Rigidity is satisfied, but where the interaction causes one to reevaluate one’s probability judgments over some partition of the possibility space without conferring certainty on any particular element. The most familiar occasion for Jeffrey conditioning is receipt of uncertain evidence: things partially perceived or remembered. But it also serves to illuminate belief updating occasioned by a change in one’s degrees of conditional belief, a kind of belief change largely ignored by classical Bayesianism. I argue that such changes in conditional belief can also be basic (in the sense of not being analyzable as a consequence of conditioning on factual information) and offer a kinematical model for a particular kind change in conditional belief. Both are applied to changes in preference. Finally, I argue that Rigidity can fail when changes of belief give inferential grounds for changes in conditional belief (and vice versa). These failures show that conditioning methods are properly regarded, not as valid rules of inference, but as tools in the ‘art of judgment’.