TL;DR
The paper challenges the traditional distinction between statistical and subjective probabilities, proposing a unified conception where all events are unique but probabilistic statements are based on statistical knowledge.
Contribution
It introduces a new conception of probability where all events are considered unique, and every statement has a probability based on statistical knowledge, applicable to rich languages.
Findings
All events are inherently unique, invalidating the statistical vs. subjective distinction.
Every statement in a language can be assigned a probability based on statistical knowledge.
The proposed conception applies to very expressive languages.
Abstract
A distinction is sometimes made between "statistical" and "subjective" probabilities. This is based on a distinction between "unique" events and "repeatable" events. We argue that this distinction is untenable, since all events are "unique" and all events belong to "kinds", and offer a conception of probability for A1 in which (1) all probabilities are based on -- possibly vague -- statistical knowledge, and (2) every statement in the language has a probability. This conception of probability can be applied to very rich languages.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRough Sets and Fuzzy Logic · Bayesian Modeling and Causal Inference · Probability and Statistical Research