Pruss, Alexander R. (2020) A Classical Way Forward for the Regularity and Normalization Problems. [Preprint]

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Abstract

Bayesian epistemology has struggled with the problem of regularity: how to deal with events that in classical probability
have zero probability. While the cases most discussed in the literature, such as infinite sequences of coin tosses or
continuous spinners, do not actually come up in scientific practice, there are cases that do come up in science. I shall
argue that these cases can be resolved without leaving the realm of classical probability, by choosing a probability measure
that preserves ``enough'' regularity. This approach also provides a resolution to the McGrew, McGrew and Vestrum normalization
problem for the fine-tuning argument.

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Item Type:	Preprint
Creators:	Creators Email ORCID Pruss, Alexander R. alexander_pruss@baylor.edu
Keywords:	probability;symmetry;regularity;normalization;fine-tuning;set theory;definability;language
Subjects:	General Issues > Confirmation/Induction Specific Sciences > Physics
Depositing User:	Dr Alexander Pruss
Date Deposited:	03 Jan 2021 14:24
Last Modified:	03 Jan 2021 14:24
Item ID:	18550
Subjects:	General Issues > Confirmation/Induction Specific Sciences > Physics
Date:	29 December 2020
URI:	https://philsci-archive.pitt.edu/id/eprint/18550

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• A Classical Way Forward for the Regularity and Normalization Problems. (deposited 03 Jan 2021 14:24) [Currently Displayed]
  • A Classical Way Forward for the Regularity and Normalization Problems. (deposited 14 Jul 2021 02:26)

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