无限域中的精确性和概率性

IF 1.8 1区 哲学 0 PHILOSOPHY MIND Pub Date : 2023-03-21 DOI:10.1093/mind/fzac053
Michael Nielsen
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引用次数: 3

摘要

概率的最佳精度论证只适用于有限域的信任函数,也就是说,信任函数最多只赋予有限个命题信任。这是一个重要的限制。它揭示了认识论中对准确性优先方案的支持比乍一看要弱得多,这意味着准确性论证还不能完成它们的竞争者——实用主义(荷兰书)论证所能完成的一切。在本文中,我研究了这种限制可以克服的程度。在有限域的最佳论证的基础上,我提出了概率的两个完全通用的精度论证——它们适用于任意域的信任函数。然后,我讨论了这些论点的前提是如何受到挑战的。我们将看到,在无限域中描述可容许的精度度量是特别困难的。
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Accuracy and Probabilism in Infinite Domains
The best accuracy arguments for probabilism apply only to credence functions with finite domains, that is, credence functions that assign credence to at most finitely many propositions. This is a significant limitation. It reveals that the support for the accuracy-first programme in epistemology is a lot weaker than it seems at first glance, and it means that accuracy arguments cannot yet accomplish everything that their competitors, the pragmatic (Dutch book) arguments, can. In this paper, I investigate the extent to which this limitation can be overcome. Building on the best arguments in finite domains, I present two accuracy arguments for probabilism that are perfectly general—they apply to credence functions with arbitrary domains. I then discuss how the arguments’ premisses can be challenged. We will see that it is particularly difficult to characterize admissible accuracy measures in infinite domains.
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来源期刊
MIND
MIND PHILOSOPHY-
CiteScore
3.10
自引率
5.60%
发文量
47
期刊介绍: Mind has long been a leading journal in philosophy. For well over 100 years it has presented the best of cutting edge thought from epistemology, metaphysics, philosophy of language, philosophy of logic, and philosophy of mind. Mind continues its tradition of excellence today. Mind has always enjoyed a strong reputation for the high standards established by its editors and receives around 350 submissions each year. The editor seeks advice from a large number of expert referees, including members of the network of Associate Editors and his international advisers. Mind is published quarterly.
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