Ever since Elga presented his famous puzzle of Sleeping Beauty, philosophers have debated between the Thirder and the Halfer positions. In his recent article, Daniel Singer proposes a new position, according to which Beauty ought to assign [0, 1/2] to the coin’s landing heads. For this argument, he exploits the similarity between Elga’s original puzzle and Bovens’s modified one. According to Singer, Beauty ought to assign the same credence to H in both versions of Sleeping Beauty. Since Beauty ought to (...) assign [0, 1/2] to H in Bovens’s version, she ought to assign [0, 1/2] to H in Elga’s original version, too. Let us call this “the Impreciser view.” In this paper, I will contend that Singer’s argument fails. First, he depends on false assumptions in defending his Impreciser view. Second, Bovens’s version of Sleeping Beauty turns out to be underdescribed in an important aspect. If we try to provide a fuller description for it, either Beauty does not have to assign [0, 1/2] to H or the thus complemented version of Bovens’s puzzle will fail to be analogous with Elga’s original one. In either case, Singer’s discussion does not establish his Impreciser view. (shrink)

Inspired by the Monty Hall Problem and a popular simple solution to it, we present a number of game-show puzzles that are analogous to the notorious Sleeping Beauty Problem (and variations on it), but much easier to solve. We replace the awakenings of Sleeping Beauty by contestants on a game show, like Monty Hall’s, and increase the number of awakenings/contestants in the same way that the number of doors in the Monty Hall Problem is increased to make it easier to (...) see what the solution to the problem is. We show that these game-show proxies for the Sleeping Beauty Problem and variations on it can be solved through simple applications of Bayes’s theorem. This means that we will phrase our analysis in terms of credences or degrees of belief. We will also rephrase our analysis, however, in terms of relative frequencies. Overall, our paper is intended to showcase, in a simple yet non-trivial example, the efficacy of a tried-and-true strategy for addressing problems in philosophy of science, i.e., develop a simple model for the problem and vary its parameters. Given that the Sleeping Beauty Problem, much more so than the Monty Hall Problem, challenges the intuitions about probabilities of many when they first encounter it, the application of this strategy to this conundrum, we believe, is pedagogically useful. (shrink)

Analyses of the Sleeping Beauty Problem are polarised between those advocating the “1/2 view” (“halfers”) and those endorsing the “1/3 view” (“thirders”). The disagreement concerns the evidential relevance of self-locating information. Unlike halfers, thirders regard self-locating information as evidentially relevant in the Sleeping Beauty Problem. In the present study, we systematically manipulate the kind of information available in different formulations of the Sleeping Beauty Problem. Our findings indicate that patterns of judgment on different formulations of the Sleeping Beauty Problem do (...) not fit either the “1/2 view” or the “1/3 view.” Human reasoners tend to acknowledge self-locating evidence as relevant, but discount its weight significantly. Accordingly, self-locating information may trigger more cautious judgments of confirmation than familiar kinds of statistical evidence. We also discuss how these results can advance the debate by providing a more nuanced and empirically grounded account or explication of the evidential impact of self-locating information. (shrink)

A perfectly rational Sleeping Beauty is put to sleep on Sunday night, and intermittently awoken either on Monday only (if a fair coin shows Heads) or on both Monday and Tuesday (if the fair coin shows Tails). According to experimental conditions, she neither remembers previous awakenings nor knows about passage of time, but she is aware of experimental conditions. Her credence for the coin having come up Heads is at the center of a scientific (mostly philosophical) controversy: halfers insist it (...) should be 1/2, while thirders claim it should be 1/3. Winkler (2017) reviewed the literature, in terminology accessible to statisticians. This paper presents a comprehensive treatment of the probability side of the problem, from the perspective of a frequentist applied statistician. Perceived contradictions are resolved (in line with Groisman 2008) or traced back to violation of model assumptions. Modeling was at the heart of the confusion and is also at the heart of the solution. (shrink)