Conditionalization Does Not Maximize Expected Accuracy

Mind 126 (504):1155-1187 (2017)
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Abstract

Greaves and Wallace argue that conditionalization maximizes expected accuracy. In this paper I show that their result only applies to a restricted range of cases. I then show that the update procedure that maximizes expected accuracy in general is one in which, upon learning P, we conditionalize, not on P, but on the proposition that we learned P. After proving this result, I provide further generalizations and show that much of the accuracy-first epistemology program is committed to KK-like iteration principles and to the existence of a class of propositions that rational agents will be certain of if and only if they are true.

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Miriam Schoenfield
University of Texas at Austin

Citations of this work

Lockeans Maximize Expected Accuracy.Kevin Dorst - 2019 - Mind 128 (509):175-211.
Updating for Externalists.J. Dmitri Gallow - 2021 - Noûs 55 (3):487-516.
Interpretations of probability.Alan Hájek - 2007 - Stanford Encyclopedia of Philosophy.
An Accuracy Based Approach to Higher Order Evidence.Miriam Schoenfield - 2018 - Philosophy and Phenomenological Research 96 (3):690-715.

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References found in this work

Knowledge and its Limits.Timothy Williamson - 2000 - Oxford University Press.
Laws and Symmetry.Bas C. Van Fraassen - 1989 - Oxford, England: Oxford University Press.
Accuracy and the Laws of Credence.Richard Pettigrew - 2016 - New York, NY.: Oxford University Press UK.
Knowledge and Its Limits.Timothy Williamson - 2000 - Philosophy 76 (297):460-464.

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