Testimony as Evidence: More Problems for Linear Pooling
Testimony as Evidence: More Problems for Linear Pooling
复制标题
证词作为证据：线性池的更多问题
DOI：
--
复制
发表时间：
2012
影响因子：
1.5
通讯作者：
K. Steele
中科院分区：
文献类型：
--
作者：
K. Steele
本文考虑了一种特殊情况下的信念更新时，代理人学习证明数据，或者换句话说，其他人的信念在一些问题。在这种情况下的兴趣是双重的：（1）线性平均法更新证词是有点流行的认识论圈，重要的是要评估其规范的可接受性，（2）这有利于更一般的调查，它意味着/要求更新方法有一个合适的贝叶斯表示（在这里作为规范标准）。本文首先针对布拉德利（Soc Choice Welf 29：609-632，2007）提出的贝叶斯兼容性问题，以及与多个证词更新相关的问题，为线性平均进行辩护。然而，这些问题的解决需要对线性平均模型的参数进行极其细致的解释--所谓的尊重权重。我们继续提出一个角色，任何“快捷”更新功能的参数应该发挥，通过这些参数的最小解释。然而，与这一角色相一致的更新函数类不包括线性平均，至少在其标准形式中是这样。
This paper considers a special case of belief updating—when an agent learns testimonial data, or in other words, the beliefs of others on some issue. The interest in this case is twofold: (1) the linear averaging method for updating on testimony is somewhat popular in epistemology circles, and it is important to assess its normative acceptability, and (2) this facilitates a more general investigation of what it means/requires for an updating method to have a suitable Bayesian representation (taken here as the normative standard). The paper initially defends linear averaging against Bayesian-compatibility concerns raised by Bradley (Soc Choice Welf 29:609–632, 2007), as well as problems associated with multiple testimony updates. The resolution of these issues, however, requires an extremely nuanced interpretation of the parameters of the linear averaging model—the so-called weights of respect. We go on to propose a role that the parameters of any ‘shortcut’ updating function should play, by way of minimal interpretation of these parameters. The class of updating functions that is consistent with this role, however, excludes linear averaging, at least in its standard form.