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Bayesian Convergence to the Truth and the Metaphysics of Possible Worlds

Published online by Cambridge University Press:  01 January 2022

Simon M. Huttegger
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Abstract

In a recent paper, Belot argues that Bayesians are epistemologically flawed because they believe with probability 1 that they will learn the truth about observational propositions in the limit. While Belot’s considerations suggest that this result should be interpreted with some care, the concerns he raises can largely be defused by putting convergence to the truth in the context of learning from an arbitrarily large but finite number of observations.

Type
Research Article
Information
Philosophy of Science , Volume 82 , Issue 4 , October 2015 , pp. 587 - 601
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

†

I would like to thank Jeff Barrett, Gordon Belot, Kenny Easwaran, Teddy Seidenfeld, and Kevin Zollman for helpful comments. I am especially grateful to Jim Joyce for providing a detailed written commentary. Special thanks also go to Brian Skyrms for a finite but very large number of discussions, extending back many years, on the nuances of convergence theorems in probability theory.

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