David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
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Philosophy of Science 77 (2):201-235 (2010)
One of the fundamental problems of epistemology is to say when the evidence in an agent’s possession justifies the beliefs she holds. In this paper and its sequel, we defend the Bayesian solution to this problem by appealing to the following fundamental norm: Accuracy An epistemic agent ought to minimize the inaccuracy of her partial beliefs. In this paper, we make this norm mathematically precise in various ways. We describe three epistemic dilemmas that an agent might face if she attempts to follow Accuracy, and we show that the only inaccuracy measures that do not give rise to such dilemmas are the quadratic inaccuracy measures. In the sequel, we derive the main tenets of Bayesianism from the relevant mathematical versions of Accuracy to which this characterization of the legitimate inaccuracy measures gives rise, but we also show that Jeffrey conditionalization has to be replaced by a different method of update in order for Accuracy to be satisfied.
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Citations of this work BETA
Richard Pettigrew (2013). A New Epistemic Utility Argument for the Principal Principle. Episteme 10 (1):19-35.
Kenny Easwaran (2015). Dr. Truthlove Or: How I Learned to Stop Worrying and Love Bayesian Probabilities. Noûs 50 (3):n/a-n/a.
Jennifer Carr (2015). Epistemic Expansions. Res Philosophica 92 (2):217-236.
Rachael Briggs (forthcoming). Foundations of Probability. Journal of Philosophical Logic:1-16.
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