发表机构
Higher School of Economics（高等经济大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文重新审视冯·米塞斯的频率解释，提出基于条件划分的修改定义，统一频率主义与贝叶斯主义，并揭示量子谜题源于概率解释不精确。
AI 中文摘要
在本文中，我重新审视了冯·米塞斯的概率频率解释，并认为尽管冯·米塞斯受到了数学家和哲学家们的严厉批评，但他的解释包含了任何科学概率连贯解释的关键要素。我提出了一种修改后的定义，该定义不基于冯·米塞斯的“无限集体”，但保留了他解释中的一个基本要素，即概率只能定量地定义在那些在相似条件下重复或可重复发生且表现出频率稳定化的事件上。新颖之处在于，所提到的“条件”应当被“划分”。因此，我将概率系统划分为对象与环境，或划分为对象、启动子系统和探测子系统，并表明这种划分解决了一系列经典问题。其他一致的解释可以与频率主义统一，例如杰恩斯式的贝叶斯主义。我详细探讨了概率那引人入胜的主观或操作主义色彩，并论证它可以建立在客观基础之上。该模型的另一个结果是，几个量子谜题可以被视为源于对概率的不精确解释。
英文摘要
In this article I revisit the frequency interpretation of probability of von Mises, and argue that it contains the key elements of any coherent interpretation of scientific probability - notwithstanding the heavy criticisms von Mises collected from mathematicians and philosophers alike. I propose a modified definition that is not based on von Mises' "infinite collectives" but retains an essential ingredient of his interpretation, namely that probability can only quantitatively be defined for events that are, or can be, repeated in similar conditions and that exhibit frequency stabilisation. New is that the mentioned "conditions" should be "partitioned". Thus, I will partition probabilistic systems into object and environment, or in object, initiating, and probing subsystem, and show that such partitioning solves a series of classic problems. Other consistent interpretations can be unified with frequentism, e.g. Bayesianism à la Jaynes. I explore in detail the tantalising subjective or operationalist touch of probability, and argue that it can be put on objective grounds. One further upshot of the model is that several quantum puzzles can be seen as deriving from an imprecise interpretation of probability.
CommentsThis is the penultimate version of Chapter 4 of my book "Problem solving in philosophy. How to do philosophy in the age of ultra-intelligent AI" (cf. https://link.springer.com/book/10.1007/978-3-032-17756-8). The present article is for 99.99% identical to the book chapter (which is the last version)
