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

Authors
Miriam Schoenfield
University of Texas at Austin
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.
Keywords Conditionalization  Accuracy  KK
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Reprint years 2017
DOI 10.1093/mind/fzw027
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References found in this work BETA

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

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Citations of this work BETA

Lockeans Maximize Expected Accuracy.Kevin Dorst - 2019 - Mind 128 (509):175-211.
Conditional Probabilities.Kenny Easwaran - 2019 - In Richard Pettigrew & Jonathan Weisberg (eds.), The Open Handbook of Formal Epistemology. PhilPapers Foundation. pp. 131-198.
The Value of Biased Information.Nilanjan Das - forthcoming - British Journal for the Philosophy of Science:axaa003.

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