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Direct inference and the sleeping beauty problem

  • Kaila DraperEmail author


This article is an attempt to use the insights of objective probability theory to solve the Sleeping Beauty problem. The approach is to develop a partial theory of direct inference and then apply that partial theory to the problem. One of the crucial components of the partial theory is the thesis that expected indefinite probabilities provide a reliable basis for direct inference. The article relies heavily on recent work by Paul D. Thorn to defend that thesis. The article’s primary conclusion is that Beauty (the perfectly rational agent of the Sleeping Beauty story) can by way of a justifiable direct inference from a statement of expected indefinite probability reach the conclusion that the epistemic probability that the relevant coin toss lands heads is 1/3. The article also provides an account of why the self-locating information that Beauty acquires on Monday is evidentially relevant to the question of whether the coin toss lands heads or tails.


Sleeping beauty problem Objective probability theory Direct inference 



I would like to thank Joel Pust for his substantial contribution to this paper.


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of PhilosophyUniversity of DelawareNewarkUSA

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