We give an analysis of the Monty Hall problem purely in terms of confirmation, without making any lottery assumptions about priors. Along the way, we show the Monty Hall problem is structurally identical to the Doomsday Argument.

The Monty Hall game is one of the most discussed decision problems, but where a convincing behavioral explanation of the systematic deviations from probability theory is still lacking. Most people not changing their initial choice, when this is beneficial under information updating, demands further explanation. Not only trust and the incentive of interestingly prolonging the game for the audience can explain this kind of behavior, but the strategic setting can be modeled more sophisticatedly. When aiming to increase the (...) odds of winning, while Monty’s incentives are unknown, then not to switch doors can be considered as the most secure strategy and avoids a sure loss when Monty’s guiding aim is not to give away the prize. Understanding and modeling the Monty Hall game can be regarded as an ideal teaching example for fundamental statistic understandings. (shrink)

The Monty Hall problem is consistently misunderstood. Mathematician Jeffrey Rosenthal argues in Monty Hall, Monty Fall, Monty Crawl” and Struck By Lightning that a proportionality principle can solve and explain the Monty Hall problem and its variants like Monty Fall and Monty Crawl better than the classic solution. Rosenthal’s Monty Fall example and solution are examined in detail. I show he has misidentified the crucial assumption in the Monty (...) Hall problem, and his own Monty Fall problem is logically equivalent to the original Monty Hall problem. I then present the Monty Fall* case where the probabilities for which door to pick post tease reveal are actually 50/50 using nothing more than Bayes’ Theorem and the standard rules of probability to prove the results—no proportionality principle is needed. The classic solution prevails as explanatorily more powerful. Finally, I show that Monty Crawl is also better explained and solved with the classic solution rather than with Rosenthal’s proportionality principle. (shrink)

Bovens (2010) points out that there is a structural analogy between the Judy Benjamin problem (JB) and the Sleeping Beauty problem (SB). On grounds of this structural analogy, he argues that both should receive the same solution, viz. the posterior probability of the eastern region of the matrix in Table 1 should equal 1/3. Hence, P*(Red) = 1/3 in the JB and P*(Heads) = 1/3 in the SB. Bovens’s argument rests on a standard error in implementing Bayesian updating, which is (...) spelled out in Shafer 1985. When we are informed of some proposition, we do not only learn the proposition in question, but also that we have learned the proposition as one of the many propositions that we might have learned. The information is generated by a protocol, which determines the various propositions that we might learn. We should then update not on the proposition in question, but rather on the fact that we learned this proposition as one of the many propositions that we might have learned. A well-known application of this insight is the Monty Hall problem (MH) as Speed (1985: 276) points out in a discussion of Shafer 1985. As an illustration, let us apply Shafer’s insight to the MH. In the MH, the contestant in a game show learns that there is a goat behind two of three doors X, Y and Z and a car behind one door. She is asked to pick one of the three doors. The contestant picks door X. Monty will then open one of the remaining doors, which he knows to have a goat behind it. Suppose Monty opens door Y. The contestant is then asked whether she wants to …. (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)

In this paper I show that Elga’s argument for a restricted principle of indifference for self-locating belief relies on the kind of mistaken reasoning that recommends the ‘staying’ strategy in the Monty Hall problem.

Peter Baumann uses the Monty Hall game to demonstrate that probabilities cannot be meaningfully applied to individual games. Baumann draws from this first conclusion a second: in a single game, it is not necessarily rational to switch from the door that I have initially chosen to the door that Monty Hall did not open. After challenging Baumann's particular arguments for these conclusions, I argue that there is a deeper problem with his position: it rests on the (...) false assumption that what justifies the switching strategy is its leading me to win a greater percentage of the time. In fact, what justifies the switching strategy is not any statistical result over the long run but rather the "causal structure" intrinsic to each individual game itself. Finally, I argue that an argument by Hilary Putnam will not help to save Baumann's second conclusion above. (shrink)

In “Judy Benjamin is a Sleeping Beauty” (2010) Bovens recognises a certain similarity between the Sleeping Beauty (SB) and the Judy Benjamin (JB). But he does not recognise the dissimilarity between underlying protocols (as spelled out in Shafer (1985). Protocols are expressed in conditional probability tables that spell out the probability of coming to learn various propositions conditional on the actual state of the world. The principle of total evidence requires that we not update on the content of the proposition (...) learned but rather on the fact that we learn the proposition in question. Now attention to protocols drives a wedge between the SB and the JB. We have shown that the solution to a close variant of the SB which involves a clear protocol is P*(Heads) = 1/3 and since Beauty’s has precisely the same information at her disposal in the original SB at the time that she is asked to state her credence for Heads, the same solution should hold. The solution to the JB, on the other hand, is dependent on Judy’s probability distribution over protocols. One reasonable protocol yields P(Red) = 1/2, but Judy could also defend alternative values or a range of values in the interval [1/3, 1/2] depending on her probability distribution over protocols. (shrink)

We conduct a laboratory experiment using the Monty Hall problem to study how simplified examples improve learning behavior and correct irrational choices in probabilistic situations. In particular, we show that after experiencing a simplified version of the MHP, subjects perform better in the MHP, compared to the control group who only experienced the 3-door version. Our results suggest that simplified examples strongly induces learning.

The Monty Hall Dilemma (MHD) is a two-step decision problem involving counterintuitive conditional probabilities. The first choice is made among three equally probable options, whereas the second choice takes place after the elimination of one of the non-selected options which does not hide the prize. Differing from most Bayesian problems, statistical information in the MHD has to be inferred, either by learning outcome probabilities or by reasoning from the presented sequence of events. This often leads to suboptimal decisions (...) and erroneous probability judgments. Specifically, decision makers commonly develop a wrong intuition that final probabilities are equally distributed, together with a preference for their first choice. Several studies have shown that repeated practice enhances sensitivity to the different reward probabilities, but does not facilitate correct Bayesian reasoning. However, modest improvements in probability judgments have been observed after guided explanations. To explain these dissociations, the present review focuses on two types of causes producing the observed biases: Emotional-based choice biases and cognitive limitations in understanding probabilistic information. Among the latter, we identify a crucial cause for the universal difficulty in overcoming the equiprobability illusion: Incomplete representation of prior and conditional probabilities. We conclude that repeated practice and/or high incentives can be effective for overcoming choice biases, but promoting an adequate partitioning of possibilities seems to be necessary for overcoming cognitive illusions and improving Bayesian reasoning. (shrink)

The Monty-Hall Problem ($MHP$) has been used to argue against a subjectivist view of Bayesianism in two ways. First, psychologists have used it to illustrate that people do not revise their degrees of belief in line with experimenters' application of Bayes' rule. Second, philosophers view $MHP$ and its two-player extension ($MHP2$) as evidence that probabilities cannot be applied to single cases. Both arguments neglect the Bayesian standpoint, which requires that $MHP2$ (studied here) be described in different terms than (...) usually applied and that the initial set of possibilities be stable (i.e., a focusing situation). This article corrects these errors and reasserts the Bayesian standpoint; namely, that the subjective probability of an event is always conditional on a belief reviser's specific current state of knowledge. (shrink)

This research examined choice behaviour and probability judgement in a counterintuitive reasoning problem called the Monty Hall problem (MHP). In Experiments 1 and 2 we examined whether learning from a simulated card game similar to the MHP affected how people solved the MHP. Results indicated that the experience with the card game affected participants' choice behaviour, in that participants selected to switch in the MHP. However, it did not affect their understanding of the objective probabilities. This suggests that (...) there is dissociation between implicit knowledge gained from the task and the explicit understanding as to why switching was the best strategy. In Experiment 3, the number of prizes and doors were manipulated to examine how participants construed the problem space of the MHP. Results revealed that participants partition the probability judgement to reflect the number of prizes over the number of unopened doors. (shrink)

Hintikka and Sandu’s independence-friendly logic is a conservative extension of first-order logic that allows one to consider semantic games with imperfect information. In the present article, we first show how several variants of the Monty Hall problem can be modeled as semantic games for IF sentences. In the process, we extend IF logic to include semantic games with chance moves and dub this extension stochastic IF logic. Finally, we use stochastic IF logic to analyze the Sleeping Beauty problem, (...) leading to the conclusion that the thirders are correct while identifying the main error in the halfers’ argument. (shrink)

The Monty Hall dilemma is a notorious probability problem with a counterintuitive solution. There is a strong tendency to stay with the initial choice, despite the fact that switching doubles the probability of winning. The current randomised experiment investigates whether feedback in a series of trials improves behavioural performance on the MHD and increases the level of understanding of the problem. Feedback was either conditional or non-conditional, and was given either in frequency format or in percentage format. Results (...) show that people learn to switch most when receiving conditional feedback in frequency format. However, problem understanding does not improve as a consequence of receiving feedback. Our study confirms the dissociation between behavioural performance on the MHD, on one hand, and actual understanding of the MHD, on the other. We discuss how this dissociation can be understood. (shrink)

In Baumann (American Philosophical Quarterly 42: 71–79, 2005) I argued that reflections on a variation of the Monty Hall problem throws a very general skeptical light on the idea of single-case probabilities. Levy (Synthese, forthcoming, 2007) puts forward some interesting objections which I answer here.

The application of probabilistic arguments to rational decisions in a single case is a contentious philosophical issue which arises in various contexts. Some authors (e.g. Horgan, Philos Pap 24:209–222, 1995; Levy, Synthese 158:139–151, 2007) affirm the normative force of probabilistic arguments in single cases while others (Baumann, Am Philos Q 42:71–79, 2005; Synthese 162:265–273, 2008) deny it. I demonstrate that both sides do not give convincing arguments for their case and propose a new account of the relationship between probabilistic reasoning (...) and rational decisions. In particular, I elaborate a flaw in Baumann’s reductio of rational single-case decisions in a modified Monty Hall Problem. (shrink)

The well known Monty Hall-problem has a clear solution if one deals with a long enough series of individual games. However, the situation is different if one switches to probabilities in a single case. This paper presents an argument for Monty Hall situations with two players (not just one, as is usual). It leads to a quite general conclusion: One cannot apply probabilistic considerations (for or against any of the strategies) to isolated single cases. If one (...) does that, one cannot but violate a very plausible non-arbitrariness condition and is led into a Moore-paradoxical incoherence. Even though arguments for switching are correct as applied to series of games, they don’t say anything useful about what rationality demands in a single case. (shrink)

Decision making theory in general, and mental models in particular, associate judgment and choice. Decision choice follows probability estimates and errors in choice derive mainly from errors in judgment. In the studies reported here we use the Monty Hall dilemma to illustrate that judgment and choice do not always go together, and that such a dissociation can lead to better decision-making. Specifically, we demonstrate that in certain decision problems, exceeding working memory limitations can actually improve decision choice. We (...) show across four experiments that increasing the number of choice alternatives forces people to collapse choices together, resulting in better decision-making. While choice performance improves, probability judgments do not change, thus demonstrating an important dissociation between choice and probability judgments. We propose the Collapsing Choice Theory (CCT) which explains how working memory capacity, probability estimation, choice alternatives, judgment, and regret all interact and effect decision quality. (shrink)

The Monty Hall Problem (MHP), a process of two-stage decision making, was presented in atypical form via a custom software game. Differing from the normal three-box MHP, the game added one additional box on-screen for each game—culminating on game 23 with 25 on-screen boxes to initially choose from. A total of 108 participants played 23 games (trials) in one of four conditions; (1) “Vanish” condition—all non-winning boxes totally removed from the screen; (2) “Empty” condition—all non-winning boxes remain on-screen, (...) but with an “empty” label on them; (3) “Steroids” condition—all non-winning boxes removed from the screen, with initially chosen box becoming 25% larger; (4) “Steroids2” condition—all non-winning boxes removed from the screen, box not currently chosen becomes 25% larger. Results indicate second-stage on-screen presence of boxes influences switching; with their absence having the opposite effect. Size manipulation appears to elicit demand characteristics resulting in indeterminate influence. (shrink)

Likelihoodists and Bayesians seem to have a fundamental disagreement about the proper probabilistic explication of relational (or contrastive) conceptions of evidential support (or confirmation). In this paper, I will survey some recent arguments and results in this area, with an eye toward pinpointing the nexus of the dispute. This will lead, first, to an important shift in the way the debate has been couched, and, second, to an alternative explication of relational support, which is in some sense a "middle way" (...) between Likelihoodism and Bayesianism. In the process, I will propose some new work for an old probability puzzle: the "Monty Hall" problem. (shrink)

Dans cet article sont commentées trois tentatives de résolution de la Belle au bois dormant, la célèbre énigme d'auto-localisation qui engendre un paradoxe probabiliste troublant : l'arbitrage fréquentiste propose une lecture ontologique des probabilités lorsque l'approche bayésienne atteint une limite ; l'analogie avec le Monty Hall s'efforce de penser de nouvelles règles de révision doxastique communes aux deux problèmes ; enfin, la leçon des compagnons encourage le partage et l'harmonisation d'estimations probabilistes entre agents rationnels. Chacun des trois arguments (...) est rappelé brièvement, puis certaines parties sont examinées plus attentivement, critiquées ou au contraire appuyées par des idées neuves, telles que la variante des Quatre Belles. (shrink)

This book will examine paradoxes in diverse areas of thought: philosophy, mathematics, physics, economics, political science, psychology, computer science, logic, statistics, linguistics, law, etc. Though the treatment of each paradox is rigorous, the book will be written accessibly with a lighthearted and humorous tone so as to keep the reader engaged. Each chapter will focus on a single paradox, structured roughly like so: 1. A question is asked in the context of a story. As an answer, the paradox is presented (...) (which often results in an aha moment). The historical background of the paradox is recounted. 2. The dénouement explains how the paradox is resolved or why there is no resolution. 3. The chapter ends with further remarks, usually contemporary real-world examples or applications of said paradox. Some examples of the paradoxes covered are the Axiom of Choice (Mathematics), Monty Hall Problem (Statistics), Morgenbesser's Paradox (Linguistics), Tea Leaves Paradox (Physics), The Ultimatum Game (Economics), and The Chicken or Egg Question (Evolution). (shrink)

This thesis addresses several questions regarding what rational agents ought to believe and how they ought to act. In the first part I begin by discussing how scientists contemplating several mutually exclusive theories, models or hypotheses can reach a rational decision regarding which one to endorse. In response to a recent argument that they cannot, I employ the tools of social choice theory to offer a ‘possibility result’ for rational theory choice. Then I utilize the tools of judgment aggregation to (...) investigate how scientists from across fields can pool their expertise together. I identify an impossibility result threatening such a procedure and prove a possibility result which requires that some scientists sometimes waive their expertise over some propositions. In the second part I first discuss the existing justifications for a restricted principle of indifference that mandates that two agents whose experiences are subjectively indistinguishable should be indifferent with respect to their identities. I argue that all existing justifications rely on the same mistaken reasoning behind the ‘staying’ strategy in the Monty Hall problem. Secondly, I show this mistake is more widespread and I identify it in arguments purporting to show the failure of two reflection-like principles. In the third part I look at a recent argument that fair policy makers face a dilemma when trying to correct a biased distributive process. I show the dilemma only holds if the correction has to happen in one-shot. Finally, I look at how we ought to design public restrooms so that we reduce the discrimination faced by minority groups. I make the case for opening our public restrooms to all genders. (shrink)

The Bayesian model has been used in psychology as the standard reference for the study of probability revision. In the first part of this paper we show that this traditional choice restricts the scope of the experimental investigation of revision to a stable universe. This is the case of a situation that, technically, is known as focusing. We argue that it is essential for a better understanding of human probability revision to consider another situation called updating (Katsuno & Mendelzon, 1992), (...) in which the universe is evolving. In that case the structure of the universe has definitely been transformed and the revision message conveys information on the resulting universe. The second part of the paper presents four experiments based on the Monty Hall puzzle that aim to show that updating is a natural frame for individuals to revise their beliefs. (shrink)

Despite the results of David Lewis, Peter Gärdenfors, and others, showing that imaging and classical conditionalization coincide only in the most trivial probabilistic models of belief revision, it turns out that imaging on a proposition A can always be described via Popper function conditionalization on a proposition that entails A. This result generalizes to any method of belief revision meeting certain minimal requirements. The proof is illustrated by an application of imaging in the context of the Monty Hall (...) Problem. (shrink)

When Archimedes, while bathing, suddenly hit upon the principle of buoyancy, he ran wildly through the streets of Syracuse, stark naked, crying "eureka!" In The Moment of Proof, Donald Benson attempts to convey to general readers the feeling of eureka--the joy of discovery--that mathematicians feel when they first encounter an elegant proof. This is not an introduction to mathematics so much as an introduction to the pleasures of mathematical thinking. And indeed the delights of this book are many and varied. (...) The book is packed with intriguing conundrums--Loyd's Fifteen Puzzle, the Petersburg Paradox, the Chaos Game, the Monty Hall Problem, the Prisoners' Dilemma--as well as many mathematical curiosities. We learn how to perform the arithmetical proof called "casting out nines" and are introduced to Russian peasant multiplication, a bizarre way to multiply numbers that actually works. The book shows us how to calculate the number of ways a chef can combine ten or fewer spices to flavor his soup (1,024) and how many people we would have to gather in a room to have a 50-50 chance of two having the same birthday (23 people). But most important, Benson takes us step by step through these many mathematical wonders, so that we arrive at the solution much the way a working scientist would--and with much the same feeling of surprise. Every fan of mathematical puzzles will be enthralled by The Moment of Proof. Indeed, anyone interested in mathematics or in scientific discovery in general will want to own this book. (shrink)

In the present paper we empirically investigate the psychometric properties of some of the most famous statistical and logical cognitive illusions from the “heuristics and biases” research program by Daniel Kahneman and Amos Tversky, who nearly 50 years ago introduced fascinating brain teasers such as the famous Linda problem, the Wason card selection task, and so-called Bayesian reasoning problems (e.g., the mammography task). In the meantime, a great number of articles has been published that empirically examine single cognitive illusions, theoretically (...) explaining people’s faulty thinking, or proposing and experimentally implementing measures to foster insight and to make these problems accessible to the human mind. Yet these problems have thus far usually been empirically analyzed on an individual-item level only (e.g., by experimentally comparing participants’ performance on various versions of one of these problems). In this paper, by contrast, we examine these illusions as a group and look at the ability to solve them as a psychological construct. Based on an sample ofN= 2,643 Luxembourgian school students of age 16–18 we investigate the internal psychometric structure of these illusions (i.e., Are they substantially correlated? Do they form a reflexive or a formative construct?), their connection to related constructs (e.g., Are they distinguishable from intelligence or mathematical competence in a confirmatory factor analysis?), and the question of which of a person’s abilities can predict the correct solution of these brain teasers (by means of a regression analysis). (shrink)

Lawrence Powers advocates a one-fallacy theory in which the only real fallacies are fallacies of ambiguity. He defines a fallacy, in general, as a bad argument that appears good. He claims that the only legitimate way that an argument can appear valid, while being invalid, is when the invalid inference is covered by an ambiguity. Several different kinds of counterexamples have been offered from begging the question, to various forms of ad hominem fallacies. In this paper, I outline three potential (...) counterexamples to Powers' theory, including one that has been addressed already by Powers, and two which are well known problems, but until now have never been applied as counterexamples to Powers' theory. I argue that there is a simpler explanation of these 'hard' cases than positing ambiguities that are not obviously there. (shrink)

Structural equations have become increasingly popular in recent years as tools for understanding causation. But standard structural equations approaches to causation face deep problems. The most philosophically interesting of these consists in their failure to incorporate a distinction between default states of an object or system, and deviations therefrom. Exploring this problem, and how to fix it, helps to illuminate the central role this distinction plays in our causal thinking.

To what extent is the scientist's endeavor qua scientist influenced by his philosophic image of himself? A preliminary and partial answer to this question is suggested by a study of eight physiological thinkers of the second half of the eighteenth century, a period during which biology was much influenced by the scientific and philosophical ideas of Isaac Newton. At this time, physiologists invoked certain "principles," "properties," and "powers" which were deemed useful as explanatory devices, even though they could not themselves (...) be explained. The use of these devices in physiology was often defended in terms of their supposed similarity to devices used in mathematics and Newtonian physics. The results of this practice are considered critically, partly in the light of current studies of scientific explanation. (shrink)

The professor announces a surprise exam for the upcoming week; her clever student purports to demonstrate by reductio that she cannot possibly give such an exam. Diagnosing his puzzling argument reveals a deeper puzzle: Is the student justified in believing the announcement? It would seem so, particularly if the upcoming 'week' is long enough. On the other hand, a plausible principle states that if, at the outset, the student is justified in believing some proposition, then he is also justified in (...) believing that he will continue to be justified in believing that proposition. It follows from this 'confidence' principle that the student is not justified in believing the announcement, regardless of the number of days in the week. I argue that the key to resolving this dilemma is to distinguish the confidence principle from a slightly weaker principle governing the student's justified degrees of belief. Representing these degrees of belief as probabilities, and taking 'justified belief' to mean 'justified degree of belief above a certain threshold', I show that we can uphold the weaker, probabilistic analog to the confidence principle, and maintain that, provided the 'week' is long enough, the student can justifiably believe the announcement. The resulting probabilistic analysis of the story leads to a new diagnosis of the logical flaw in the student's reasoning, and suggests, finally, that even those early stages of it which are logically impeccable exhibit another kind of flaw: circularity. (shrink)

Contemporary philosophical work on causation is a tangled mess of disparate aims, approaches, and accounts. Best to cut through it by means of ruthless but, hopefully, sensible judgments. The ones that follow are designed to sketch the most fruitful avenues for future work.

Lewis's work on causation was governed by a familiar methodological approach: the aim was to come up with an account of causation that would recover, in as elegant a fashion as possible, all of our firm “pre‐theoretic” intuitions about hypothetical cases. That methodology faces an obvious challenge, in that it is not clear why anyone not interested in the semantics of the English word “cause” should care about its results. Better to take a different approach, one which treats our intuitions (...) about cases merely as guides in the construction of a causal concept or concepts that will serve some useful theoretical purpose. I sketch one central such purpose, suggesting, first, that an account of causation that, like Lewis's, gives a central role to counterfactuals is well‐suited to fulfill it, and, second, that the most famous pre‐emption‐based counterexamples to a counterfactual account yield an important constraint on a successful account. (shrink)

The Tree of Life has traditionally been understood to represent the history of species lineages. However, recently researchers have suggested that it might be better interpreted as representing the history of cellular lineages, sometimes called the Tree of Cells. This paper examines and evaluates reasons offered against this cellular interpretation of the Tree of Life. It argues that some such reasons are bad reasons, based either on a false attribution of essentialism, on a misunderstanding of the problem of lineage identity, (...) or on a limited view of scientific representation. I suggest that debate about the Tree of Cells and other successors to the traditional Tree of Life should be formulated in terms of the purposes these representations may serve. In pursuing this strategy, we see that the Tree of Cells cannot serve one purpose suggested for it: as an explanation for the hierarchical nature of taxonomy. We then explore whether, instead, the tree may play an important role in the dynamic modeling of evolution. As highly-integrated complex systems, cells may influence which lineage components can successfully transfer into them and how they change once integrated. Only if they do in fact have a substantial role to play in this process might the Tree of Cells have some claim to be the Tree of Life. (shrink)

As research therapists with hundreds of hours of clinical experience supporting adults with PTSD in Phase 3 trials of MDMA assisted-therapy (MAT), we appreciate the opportunity to respond to this s...