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  1. The Rational Group.Franz Dietrich - manuscript
    Can a group be a standard rational agent? This would require the group to hold aggregate preferences which maximise expected utility and change only by Bayesian updating. Group rationality is possible, but the only preference aggregation rules which support it (and are minimally Paretian and continuous) are the linear-geometric rules, which combine individual tastes linearly and individual beliefs geometrically.
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  2. Incomplete Preference and Indeterminate Comparative Probability.Yang Liu - forthcoming - British Journal for the Philosophy of Science:axaa009.
    The notion of comparative probability defined in Bayesian subjectivist theory stems from an intuitive idea that, for a given pair of events, one event may be considered “more probable” than the other. Yet it is conceivable that there are cases where it is indeterminate as to which event is more probable, due to, e.g., lack of robust statistical information. We take that these cases involve indeterminate comparative probabilities. This paper provides a Savage-style decision-theoretic foundation for indeterminate comparative probabilities.
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  3. Epistemic Decision Theory's Reckoning.Conor Mayo-Wilson & Gregory Wheeler - manuscript
    Epistemic decision theory (EDT) employs the mathematical tools of rational choice theory to justify epistemic norms, including probabilism, conditionalization, and the Principal Principle, among others. Practitioners of EDT endorse two theses: (1) epistemic value is distinct from subjective preference, and (2) belief and epistemic value can be numerically quantified. We argue the first thesis, which we call epistemic puritanism, undermines the second.
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  4. Obligation, Permission, and Bayesian Orgulity.Michael Nielsen & Rush T. Stewart - 2019 - Ergo: An Open Access Journal of Philosophy 6.
    This essay has two aims. The first is to correct an increasingly popular way of misunderstanding Belot's Orgulity Argument. The Orgulity Argument charges Bayesianism with defect as a normative epistemology. For concreteness, our argument focuses on Cisewski et al.'s recent rejoinder to Belot. The conditions that underwrite their version of the argument are too strong and Belot does not endorse them on our reading. A more compelling version of the Orgulity Argument than Cisewski et al. present is available, however---a point (...)
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  5. Independent Opinions? On the Causal Foundations of Belief Formation and Jury Theorems.Franz Dietrich & Kai Spiekermann - 2013 - Mind 122 (487):655-685.
    Democratic decision-making is often defended on grounds of the ‘wisdom of crowds’: decisions are more likely to be correct if they are based on many independent opinions, so a typical argument in social epistemology. But what does it mean to have independent opinions? Opinions can be probabilistically dependent even if individuals form their opinion in causal isolation from each other. We distinguish four probabilistic notions of opinion independence. Which of them holds depends on how individuals are causally affected by environmental (...)
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  6. Bayesian Decision Theory and Stochastic Independence.Philippe Mongin - 2017 - TARK 2017.
    Stochastic independence has a complex status in probability theory. It is not part of the definition of a probability measure, but it is nonetheless an essential property for the mathematical development of this theory. Bayesian decision theorists such as Savage can be criticized for being silent about stochastic independence. From their current preference axioms, they can derive no more than the definitional properties of a probability measure. In a new framework of twofold uncertainty, we introduce preference axioms that entail not (...)
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  7. An Observation on Carnapʼs Continuum and Stochastic Independencies.J. B. Paris - 2013 - Journal of Applied Logic 11 (4):421-429.
    We characterize those identities and independencies which hold for all probability functions on a unary language satisfying the Principle of Atom Exchangeability. We then show that if this is strengthen to the requirement that Johnson's Sufficientness Principle holds, thus giving Carnap's Continuum of inductive methods for languages with at least two predicates, then new and somewhat inexplicable identities and independencies emerge, the latter even in the case of Carnap's Continuum for the language with just a single predicate.
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  8. You Can’T Always Get What You Want: Some Considerations Regarding Conditional Probabilities.Wayne C. Myrvold - 2015 - Erkenntnis 80 (3):573-603.
    The standard treatment of conditional probability leaves conditional probability undefined when the conditioning proposition has zero probability. Nonetheless, some find the option of extending the scope of conditional probability to include zero-probability conditions attractive or even compelling. This article reviews some of the pitfalls associated with this move, and concludes that, for the most part, probabilities conditional on zero-probability propositions are more trouble than they are worth.
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  9. The Paradox of the Bayesian Experts.Philippe Mongin - 2001 - In David Corfield & Jon Williamson (eds.), Foundations of Bayesianism. Kluwer Academic Publishers. pp. 309-338.
    This paper (first published under the same title in Journal of Mathematical Economics, 29, 1998, p. 331-361) is a sequel to "Consistent Bayesian Aggregation", Journal of Economic Theory, 66, 1995, p. 313-351, by the same author. Both papers examine mathematically whether the the following assumptions are compatible: the individuals and the group both form their preferences according to Subjective Expected Utility (SEU) theory, and the preferences of the group satisfy the Pareto principle with respect to those of the individuals. While (...)
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Betting Interpretations and Dutch Books
  1. Bayesian Updating When What You Take Yourself to Learn Might Be False.Richard Pettigrew - manuscript
    Michael Rescorla (2020) has recently pointed out that the standard arguments for Bayesian Conditionalization assume that whenever you take yourself to learn something with certainty, it's true. Most people would reject this assumption. In response, Rescorla offers an improved Dutch Book argument for Bayesian Conditionalization that does not make this assumption. My purpose in this paper is two-fold. First, I want to illuminate Rescorla's new argument by giving a very general Dutch Book argument that applies to many cases of updating (...)
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  2. Measuring Belief and Risk Attitude.Sven Neth - 2019 - Electronic Proceedings in Theoretical Computer Science 297:252–272.
    Ramsey (1926) sketches a proposal for measuring the subjective probabilities of an agent by their observable preferences, assuming that the agent is an expected utility maximizer. I show how to extend the spirit of Ramsey's method to a strictly wider class of agents: risk-weighted expected utility maximizers (Buchak 2013). In particular, I show how we can measure the risk attitudes of an agent by their observable preferences, assuming that the agent is a risk-weighted expected utility maximizer. Further, we can leverage (...)
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  3. Betting Against the Zen Monk: On Preferences and Partial Belief.Edward Elliott - forthcoming - Synthese:1-26.
    According to the preference-centric approach to understanding partial belief, the connection between partial beliefs and preferences is key to understanding what partial beliefs are and how they’re measured. As Ramsey put it, the ‘degree of a belief is a causal property of it, which we can express vaguely as the extent to which we are prepared to act on it’ The Foundations of Mathematics and Other Logical Essays, Routledge, Oxon, pp 156–198, 1931). But this idea is not as popular as (...)
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  4. The Problem of State-Dependent Utility: A Reappraisal.Jean Baccelli - forthcoming - British Journal for the Philosophy of Science:axz024.
    State-dependent utility is a problem for the behavioural branch of decision theory under uncertainty. It questions the very possibility that beliefs be revealed by choice data. According to the current literature, all models of beliefs are equally exposed to the problem. Moreover, the problem is solvable only when the decision-maker can influence the resolution of uncertainty. This article gives grounds to reject these two views. The various models of beliefs can be shown to be unequally exposed to the problem of (...)
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  5. Beauty, Odds, and Credence.Masahiro Yamada - 2019 - Philosophical Studies 176 (5):1247-1261.
    This paper considers fair betting odds for certain bets that might be placed in the situation discussed in the so-called Sleeping Beauty Problem. This paper examines what Thirders, Halfers, and Double Halfers must say about the odds as determined by various decision theoretic approaches and argues that Thirders and Halfers have difficulties formulating plausible and coherent positions concerning the relevant betting odds. Double Halfers do not face this problem and that is an important consideration in favor of Double Halfers.
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  6. Moral Hazard, the Savage Framework, and State-Dependent Utility.Jean Baccelli - forthcoming - Erkenntnis:1-21.
    In this paper, I investigate the betting behavior of a decision-maker who can influence the likelihood of the events upon which she is betting. In decision theory, this is best known as a situation of moral hazard. Focusing on a particularly simple case, I sketch the first systematic analysis of moral hazard in the canonical Savage framework. From the results of this analysis, I draw two philosophical conclusions. First, from an observational and a descriptive point of view, there need to (...)
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  7. On the Expected Utility Objection to the Dutch Book Argument for Probabilism.Richard Pettigrew - 2019 - Noûs 1.
    The Dutch Book Argument for Probabilism assumes Ramsey's Thesis (RT), which purports to determine the prices an agent is rationally required to pay for a bet. Recently, a new objection to Ramsey's Thesis has emerged (Hedden 2013, Wronski & Godziszewski 2017, Wronski 2018)--I call this the Expected Utility Objection. According to this objection, it is Maximise Subjective Expected Utility (MSEU) that determines the prices an agent is required to pay for a bet, and this often disagrees with Ramsey's Thesis. I (...)
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  8. Do Bets Reveal Beliefs?Jean Baccelli - 2017 - Synthese 194 (9):3393-3419.
    This paper examines the preference-based approach to the identification of beliefs. It focuses on the main problem to which this approach is exposed, namely that of state-dependent utility. First, the problem is illustrated in full detail. Four types of state-dependent utility issues are distinguished. Second, a comprehensive strategy for identifying beliefs under state-dependent utility is presented and discussed. For the problem to be solved following this strategy, however, preferences need to extend beyond choices. We claim that this a necessary feature (...)
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  9. A Dutch Book Theorem for Quantificational Credences.Benjamin Lennertz - 2017 - Ergo: An Open Access Journal of Philosophy 4.
    In this paper, I present an argument for a rational norm involving a kind of credal attitude called a quantificational credence – the kind of attitude we can report by saying that Lucy thinks that each record in Schroeder’s collection is 5% likely to be scratched. I prove a result called a Dutch Book Theorem, which constitutes conditional support for the norm. Though Dutch Book Theorems exist for norms on ordinary and conditional credences, there is controversy about the epistemic significance (...)
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  10. Deductive Reasoning Under Uncertainty: A Water Tank Analogy.Guy Politzer - 2016 - Erkenntnis 81 (3):479-506.
    This paper describes a cubic water tank equipped with a movable partition receiving various amounts of liquid used to represent joint probability distributions. This device is applied to the investigation of deductive inferences under uncertainty. The analogy is exploited to determine by qualitative reasoning the limits in probability of the conclusion of twenty basic deductive arguments (such as Modus Ponens, And-introduction, Contraposition, etc.) often used as benchmark problems by the various theoretical approaches to reasoning under uncertainty. The probability bounds imposed (...)
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  11. When Betting Odds and Credences Come Apart: More Worries for Dutch Book Arguments.Darren Bradley & Hannes Leitgeb - 2006 - Analysis 66 (2):119-127.
    If an agent believes that the probability of E being true is 1/2, should she accept a bet on E at even odds or better? Yes, but only given certain conditions. This paper is about what those conditions are. In particular, we think that there is a condition that has been overlooked so far in the literature. We discovered it in response to a paper by Hitchcock (2004) in which he argues for the 1/3 answer to the Sleeping Beauty problem. (...)
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  12. Frank Plumpton Ramsey.Brad Armendt - 2005 - In Sahotra Sarkar & Jessica Pfeifer (eds.), The Philosophy of Science: An Encyclopedia. Routledge. pp. 671-681.
    On the work of Frank Ramsey, emphasizing topics most relevant to philosophy of science.
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  13. A New Way to Block a Dutch Book Argument, or The Stubborn Non-Probabilist.Leszek Wronski - manuscript
    We point out a yet unnoticed flaw in Dutch Book arguments that relates to a link between degrees of belief and betting quotients. We offer a set of precise conditions governing when a nonprobabilist is immune to the classical Dutch Book argument. We suggest that diachronic Dutch Book arguments are also affected.
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  14. A Utility Based Evaluation of Logico-Probabilistic Systems.Paul D. Thorn & Gerhard Schurz - 2014 - Studia Logica 102 (4):867-890.
    Systems of logico-probabilistic (LP) reasoning characterize inference from conditional assertions interpreted as expressing high conditional probabilities. In the present article, we investigate four prominent LP systems (namely, systems O, P, Z, and QC) by means of computer simulations. The results reported here extend our previous work in this area, and evaluate the four systems in terms of the expected utility of the dispositions to act that derive from the conclusions that the systems license. In addition to conforming to the dominant (...)
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  15. Cognitivist Probabilism.Paul D. Thorn - 2013 - In Vit Punochar & Petr Svarny (eds.), The Logica Yearbook 2012. College Publications. pp. 201-213.
    In this article, I introduce the term “cognitivism” as a name for the thesis that degrees of belief are equivalent to full beliefs about truth-valued propositions. The thesis (of cognitivism) that degrees of belief are equivalent to full beliefs is equivocal, inasmuch as different sorts of equivalence may be postulated between degrees of belief and full beliefs. The simplest sort of equivalence (and the sort of equivalence that I discuss here) identifies having a given degree of belief with having a (...)
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  16. Against the Possibility of a Formal Account of Rationality.Shivaram Lingamneni - manuscript
    I analyze a recent exchange between Adam Elga and Julian Jonker concerning unsharp (or imprecise) credences and decision-making over them. Elga holds that unsharp credences are necessarily irrational; I agree with Jonker's reply that they can be rational as long as the agent switches to a nonlinear valuation. Through the lens of computational complexity theory, I then argue that even though nonlinear valuations can be rational, they come in general at the price of computational intractability, and that this problematizes their (...)
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  17. Dutch Book Arguments and Imprecise Probabilities.Seamus Bradley - 2012 - In Dennis Dieks, Stephan Hartmann, Michael Stoeltzner & Marcel Weber (eds.), Probabilities, Laws and Structures. Springer.
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  18. Laying Sleeping Beauty to Rest.Masahiro Yamada - manuscript
    There are three main points of the paper. 1. There are straightforward ways of manipulating expected gains and losses that result in a divergence between fair betting odds and credence. Such manipulations are familiar from tools of finance. One can easily see that the Sleeping Beauty case is structured in such a way as to result in a divergence between fair betting odds and credence. 2. The inspection of credences and betting odds in certain betting situations shows that the two (...)
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  19. Generalized Probabilism: Dutch Books and Accuracy Domi- Nation.J. Robert G. Williams - 2012 - Journal of Philosophical Logic 41 (5):811-840.
    Jeff Paris proves a generalized Dutch Book theorem. If a belief state is not a generalized probability then one faces ‘sure loss’ books of bets. In Williams I showed that Joyce’s accuracy-domination theorem applies to the same set of generalized probabilities. What is the relationship between these two results? This note shows that both results are easy corollaries of the core result that Paris appeals to in proving his dutch book theorem. We see that every point of accuracy-domination defines a (...)
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  20. Conditionalization and Belief De Se.Darren Bradley - 2010 - Dialectica 64 (2):247-250.
    Colin Howson (1995 ) offers a counter-example to the rule of conditionalization. I will argue that the counter-example doesn't hit its target. The problem is that Howson mis-describes the total evidence the agent has. In particular, Howson overlooks how the restriction that the agent learn 'E and nothing else' interacts with the de se evidence 'I have learnt E'.
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  21. Stakes and Beliefs.Brad Armendt - 2010 - Philosophical Studies 147 (1):71 - 87.
    The idea that beliefs may be stake-sensitive is explored. This is the idea that the strength with which a single, persistent belief is held may vary and depend upon what the believer takes to be at stake. The stakes in question are tied to the truth of the belief—not, as in Pascal’s wager and other cases, to the belief’s presence. Categorical beliefs and degrees of belief are considered; both kinds of account typically exclude the idea and treat belief as stake-invariant (...)
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  22. Dutch Books, Additivity, and Utility Theory.Brad Armendt - 1993 - Philosophical Topics 21 (1):1-20.
    One guide to an argument's significance is the number and variety of refutations it attracts. By this measure, the Dutch book argument has considerable importance.2 Of course this measure alone is not a sure guide to locating arguments deserving of our attention—if a decisive refutation has really been given, we are better off pursuing other topics. But the presence of many and varied counterarguments at least suggests that either the refutations are controversial, or that their target admits of more than (...)
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  23. Is There a Dutch Book Argument for Probability Kinematics?Brad Armendt - 1980 - Philosophy of Science 47 (4):583-588.
    Dutch Book arguments have been presented for static belief systems and for belief change by conditionalization. An argument is given here that a rule for belief change which under certain conditions violates probability kinematics will leave the agent open to a Dutch Book.
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  24. Countable Additivity and the de Finetti Lottery.Paul Bartha - 2004 - British Journal for the Philosophy of Science 55 (2):301-321.
    De Finetti would claim that we can make sense of a draw in which each positive integer has equal probability of winning. This requires a uniform probability distribution over the natural numbers, violating countable additivity. Countable additivity thus appears not to be a fundamental constraint on subjective probability. It does, however, seem mandated by Dutch Book arguments similar to those that support the other axioms of the probability calculus as compulsory for subjective interpretations. These two lines of reasoning can be (...)
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  25. Dutch Books and Infinity.Brian Weatherson - manuscript
    Peter Walley argues that a vague credal state need not be representable by a set of probability functions that could represent precise credal states, because he believes that the members of the representor set need not be countably additive. I argue that the states he defends are in a way incoherent.
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Conditional Probability
  1. Improving Bayesian Statistics Understanding in the Age of Big Data with the Bayesvl R Package.Quan-Hoang Vuong, Viet-Phuong La, Minh-Hoang Nguyen, Manh-Toan Ho, Manh-Tung Ho & Peter Mantello - 2020 - Software Impacts 4 (1):100016.
    The exponential growth of social data both in volume and complexity has increasingly exposed many of the shortcomings of the conventional frequentist approach to statistics. The scientific community has called for careful usage of the approach and its inference. Meanwhile, the alternative method, Bayesian statistics, still faces considerable barriers toward a more widespread application. The bayesvl R package is an open program, designed for implementing Bayesian modeling and analysis using the Stan language’s no-U-turn (NUTS) sampler. The package combines the ability (...)
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  2. Self-Locating Belief and Updating on Learning.Darren Bradley - 2020 - Mind 129 (514):579-584.
    Self-locating beliefs cause a problem for conditionalization. Miriam Schoenfield offers a solution: that on learning E, agents should update on the fact that they learned E. However, Schoenfield is not explicit about whether the fact that they learned E is self-locating. I will argue that if the fact that they learned E is self-locating then the original problem has not been addressed, and if the fact that they learned E is not self-locating then the theory generates implausible verdicts which Schoenfield (...)
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  3. Tiến triển của bayesvl kể từ sau khi xuất bản trên CRAN.Vương Quân Hoàng & Lã Việt Phương - manuscript
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  4. Papineau's Philosophical Devices [Review]. [REVIEW]Matheus Silva - 2012 - Fundamento 5:147-150.
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  5. The Triviality Result is Not Counter-Intuitive.Matheus Silva - manuscript
    The Equation (TE) states that the probability of A → B is the probability of B given A (Jeffrey, 1964: 702–703). Lewis has shown that the acceptance of TE implies that the probability of A → B is the probability of B, which is implausible: the probability of a conditional cannot plausibly be the same as the probability of its consequent, e.g., the probability that the match will light given that is struck is not intuitively the same as the probability (...)
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  6. The Structure of Epistemic Probabilities.Nevin Climenhaga - 2019 - Philosophical Studies:1-30.
    The epistemic probability of A given B is the degree to which B evidentially supports A, or makes A plausible. This paper is a first step in answering the question of what determines the values of epistemic probabilities. I break this question into two parts: the structural question and the substantive question. Just as an object’s weight is determined by its mass and gravitational acceleration, some probabilities are determined by other, more basic ones. The structural question asks what probabilities are (...)
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  7. Counterexamples to Some Characterizations of Dilation.Michael Nielsen & Rush T. Stewart - 2019 - Erkenntnis:1-12.
    Pedersen and Wheeler (2014) and Pedersen and Wheeler (2015) offer a wide-ranging and in-depth exploration of the phenomenon of dilation. We find that these studies raise many interesting and important points. However, purportedly general characterizations of dilation are reported in them that, unfortunately, admit counterexamples. The purpose of this note is to show in some detail that these characterization results are false.
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  8. A Theory of Bayesian Groups.Franz Dietrich - 2019 - Noûs 53 (3):708-736.
    A group is often construed as one agent with its own probabilistic beliefs (credences), which are obtained by aggregating those of the individuals, for instance through averaging. In their celebrated “Groupthink”, Russell et al. (2015) require group credences to undergo Bayesian revision whenever new information is learnt, i.e., whenever individual credences undergo Bayesian revision based on this information. To obtain a fully Bayesian group, one should often extend this requirement to non-public or even private information (learnt by not all or (...)
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  9. Another Approach to Consensus and Maximally Informed Opinions with Increasing Evidence.Rush T. Stewart & Michael Nielsen - 2018 - Philosophy of Science (2):236-254.
    Merging of opinions results underwrite Bayesian rejoinders to complaints about the subjective nature of personal probability. Such results establish that sufficiently similar priors achieve consensus in the long run when fed the same increasing stream of evidence. Initial subjectivity, the line goes, is of mere transient significance, giving way to intersubjective agreement eventually. Here, we establish a merging result for sets of probability measures that are updated by Jeffrey conditioning. This generalizes a number of different merging results in the literature. (...)
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  10. Qualitative Probabilistic Inference Under Varied Entropy Levels.Paul D. Thorn & Gerhard Schurz - 2016 - Journal of Applied Logic 19 (2):87-101.
    In previous work, we studied four well known systems of qualitative probabilistic inference, and presented data from computer simulations in an attempt to illustrate the performance of the systems. These simulations evaluated the four systems in terms of their tendency to license inference to accurate and informative conclusions, given incomplete information about a randomly selected probability distribution. In our earlier work, the procedure used in generating the unknown probability distribution (representing the true stochastic state of the world) tended to yield (...)
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  11. Conditional Probability and Defeat.Trenton Merricks - 2002 - In James Beilby (ed.), Naturalism Defeated? Essays on Plantinga's Evolutionary Argument Against Naturalism. Cornell University Press. pp. 165-175.
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  12. Stalnaker’s Thesis in Context.Andrew Bacon - 2015 - Review of Symbolic Logic 8 (1):131-163.
    In this paper I present a precise version of Stalnaker's thesis and show that it is both consistent and predicts our intuitive judgments about the probabilities of conditionals. The thesis states that someone whose total evidence is E should have the same credence in the proposition expressed by 'if A then B' in a context where E is salient as they have conditional credence in the proposition B expresses given the proposition A expresses in that context. The thesis is formalised (...)
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  13. Belief Revision Generalized: A Joint Characterization of Bayes's and Jeffrey's Rules.Franz Dietrich, Christian List & Richard Bradley - 2016 - Journal of Economic Theory 162:352-371.
    We present a general framework for representing belief-revision rules and use it to characterize Bayes's rule as a classical example and Jeffrey's rule as a non-classical one. In Jeffrey's rule, the input to a belief revision is not simply the information that some event has occurred, as in Bayes's rule, but a new assignment of probabilities to some events. Despite their differences, Bayes's and Jeffrey's rules can be characterized in terms of the same axioms: "responsiveness", which requires that revised beliefs (...)
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  14. Revealing the Beauty Behind the Sleeping Beauty Problem.Ioannis Mariolis - manuscript
    A large number of essays address the Sleeping Beauty problem, which undermines the validity of Bayesian inference and Bas Van Fraassen's 'Reflection Principle'. In this study a straightforward analysis of the problem based on probability theory is presented. The key difference from previous works is that apart from the random experiment imposed by the problem's description, a different one is also considered, in order to negate the confusion on the involved conditional probabilities. The results of the analysis indicate that no (...)
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  15. You Can’T Always Get What You Want: Some Considerations Regarding Conditional Probabilities.Wayne C. Myrvold - 2015 - Erkenntnis 80 (3):573-603.
    The standard treatment of conditional probability leaves conditional probability undefined when the conditioning proposition has zero probability. Nonetheless, some find the option of extending the scope of conditional probability to include zero-probability conditions attractive or even compelling. This article reviews some of the pitfalls associated with this move, and concludes that, for the most part, probabilities conditional on zero-probability propositions are more trouble than they are worth.
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  16. How to Analyse Retrodictive Probabilities in Inference to the Best Explanation.Andrew Holster - manuscript
    IBE ('Inference to the best explanation' or abduction) is a popular and highly plausible theory of how we should judge the evidence for claims of past events based on present evidence. It has been notably developed and supported recently by Meyer following Lipton. I believe this theory is essentially correct. This paper supports IBE from a probability perspective, and argues that the retrodictive probabilities involved in such inferences should be analysed in terms of predictive probabilities and a priori probability ratios (...)
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1 — 50 / 211