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.

中文翻译：

---

无限域中的准确性和概率

概率论的最佳准确性论证仅适用于具有有限域的可信度函数，即，将可信度分配给至多有限多个命题的可信度函数。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看起来要弱得多，这意味着准确性论证还不能完成其竞争对手实用主义（荷兰书）论证所能做到的一切。在本文中，我研究了可以克服这种限制的程度。基于有限域中的最佳论据，我提出了两个非常普遍的概率论准确性论据——它们适用于具有任意域的可信度函数。然后我讨论如何挑战论证的前提。