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  1. added 2020-05-20
    Trung tâm ISR có bài ra mừng 130 năm Ngày sinh Chủ tịch Hồ Chí Minh.Hồ Mạnh Toàn - 2020 - ISR Phenikaa 2020 (5):1-3.
    Bài mới xuất bản vào ngày 19-5-2020 với tác giả liên lạc là NCS Nguyễn Minh Hoàng, cán bộ nghiên cứu của Trung tâm ISR, trình bày tiếp cận thống kê Bayesian cho việc nghiên cứu dữ liệu khoa học xã hội. Đây là kết quả của định hướng Nhóm nghiên cứu SDAG được nêu rõ ngay từ ngày 18-5-2019.
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  2. added 2020-05-02
    On the Probability of Plenitude.Jeffrey Sanford Russell - forthcoming - Journal of Philosophy.
    I examine what the mathematical theory of random structures can teach us about the probability of Plenitude, a thesis closely related to David Lewis's modal realism. Given some natural assumptions, Plenitude is reasonably probable a priori, but in principle it can be (and plausibly it has been) empirically disconfirmed—not by any general qualitative evidence, but rather by our de re evidence.
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  3. added 2020-04-30
    The Principle of Indifference and the Principal Principle Are Incompatible.J. Dmitri Gallow - manuscript
    The Principle of Indifference (POI) says that, in the absence of evidence, you should distribute your credences evenly. The Principal Principle (PP) says that, in the absence of evidence, you should align your credences with the chances. Richard Pettigrew (2016) appears to accept both the PP and the POI. Many other authors write as though Bayesians are free to accept both of these principles. Hawthorne et. al. (2017) even go so far as to argue that the PP implies the POI. (...)
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  4. added 2020-03-02
    R Codes for Preliminary Checks (Bayesian Method).Quan-Hoang Vuong - 2018 - SSHPA-AISDL 2018 (1):1-5.
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  5. added 2020-02-20
    Richard Bradley, "Decision Theory with a Human Face.". [REVIEW]William John Peden - 2020 - Philosophy in Review 40 (1):4-6.
    A non-expert who struggles to make good decisions and who turns to decision theory for help, might be more than a little surprised by what they find. If they read a standard treatment of the subject, they will find that they are assumed to be logically omniscient: they know all the logical facts about the propositions whose truth they have considered. Their beliefs are also assumed to be logically closed: if they believe each of a set of propositions S, then (...)
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  6. added 2020-02-18
    Bayesian Beauty.Silvia Milano - forthcoming - Erkenntnis:1-20.
    The Sleeping Beauty problem has attracted considerable attention in the literature as a paradigmatic example of how self-locating uncertainty creates problems for the Bayesian principles of Conditionalization and Reflection. Furthermore, it is also thought to raise serious issues for diachronic Dutch Book arguments. I show that, contrary to what is commonly accepted, it is possible to represent the Sleeping Beauty problem within a standard Bayesian framework. Once the problem is correctly represented, the ‘thirder’ solution satisfies standard rationality principles, vindicating why (...)
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  7. added 2020-02-07
    Naturalness as a Constraint on Priors.Darren Bradley - 2020 - Mind 129 (513):179-203.
    Many epistemological problems can be solved by the objective Bayesian view that there are rationality constraints on priors, that is, inductive probabilities. But attempts to work out these constraints have run into such serious problems that many have rejected objective Bayesianism altogether. I argue that the epistemologist should borrow the metaphysician’s concept of naturalness and assign higher priors to more natural hypotheses.
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  8. added 2020-02-07
    Impermissive Bayesianism.Christopher Meacham - 2013 - Erkenntnis 79 (Suppl 6):1185-1217.
    This paper examines the debate between permissive and impermissive forms of Bayesianism. It briefly discusses some considerations that might be offered by both sides of the debate, and then replies to some new arguments in favor of impermissivism offered by Roger White. First, it argues that White’s defense of Indifference Principles is unsuccessful. Second, it contends that White’s arguments against permissive views do not succeed.
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  9. added 2019-12-13
    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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  10. added 2019-09-08
    Are Non-Accidental Regularities a Cosmic Coincidence? Revisiting a Central Threat to Humean Laws.Aldo Filomeno - forthcoming - Synthese:1-1.
    If the laws of nature are as the Humean believes, it is an unexplained cosmic coincidence that the actual Humean mosaic is as extremely regular as it is. This is a strong and well-known objection to the Humean account of laws. Yet, as reasonable as this objection may seem, it is nowadays sometimes dismissed. The reason: its unjustified implicit assignment of equiprobability to each possible Humean mosaic; that is, its assumption of the principle of indifference, which has been attacked on (...)
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  11. added 2019-06-05
    Bayesianism and Inference to the Best Explanation.Valeriano Iranzo - 2008 - Theoria : An International Journal for Theory, History and Fundations of Science 23 (1):89-106.
    Bayesianism and Inference to the best explanation are two different models of inference. Recently there has been some debate about the possibility of “bayesianizing” IBE. Firstly I explore several alternatives to include explanatory considerations in Bayes’s Theorem. Then I distinguish two different interpretations of prior probabilities: “IBE-Bayesianism” and “frequentist-Bayesianism”. After detailing the content of the latter, I propose a rule for assessing the priors. I also argue that Freq-Bay: endorses a role for explanatory value in the assessment of scientific hypotheses; (...)
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  12. added 2019-01-09
    Twierdzenie Bayesa w projektowaniu strategii diagnostycznych w medycynie.Tomasz Rzepiński - 2018 - Diametros 57:39-60.
    The paper will compare two methods used in the design of diagnostic strategies. The first one is a method that precises predictive value of diagnostic tests. The second one is based on the use of Bayes’ theorem. The main aim of this article is to identify the epistemological assumptions underlying both of these methods. For the purpose of this objective, example projects of one and multi-stage diagnostic strategy developed using both methods will be considered.
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  13. added 2018-09-06
    Précis of Accuracy and the Laws of Credence.Richard Pettigrew - 2018 - Philosophy and Phenomenological Research 96 (3):749-754.
  14. added 2018-03-11
    A Critical Introduction to Formal Epistemology.Darren Bradley - 2015 - London: Bloomsbury.
  15. added 2018-02-12
    The Imprecise Impermissivist’s Dilemma.Clinton Castro & Casey Hart - 2019 - Synthese 196 (4):1623-1640.
    Impermissivists hold that an agent with a given body of evidence has at most one rationally permitted attitude that she should adopt towards any particular proposition. Permissivists deny this, often motivating permissivism by describing scenarios that pump our intuitions that the agent could reasonably take one of several attitudes toward some proposition. We criticize the following impermissivist response: while it seems like any of that range of attitudes is permissible, what is actually required is the single broad attitude that encompasses (...)
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  16. added 2017-09-05
    The Bayesian and the Dogmatist.Brian Weatherson - 2007 - Proceedings of the Aristotelian Society 107 (1pt2):169-185.
    Dogmatism is sometimes thought to be incompatible with Bayesian models of rational learning. I show that the best model for updating imprecise credences is compatible with dogmatism.
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  17. added 2017-05-02
    By Parallel Reasoning: The Construction and Evaluation of Analogical Arguments.Paul Bartha - 2010 - Oxford University Press.
    Analogical arguments -- Philosophical theories -- Computational theories -- The articulation model -- Analogies in mathematics -- Similarity and patterns of generalization -- Analogy and epistemic values -- Analogy and symmetry -- A wider role for analogies.
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  18. added 2017-03-13
    Carnap’s Epistemological Critique of Metaphysics.Darren Bradley - 2018 - Synthese 195 (5):2247-2265.
    Many who take a dismissive attitude towards metaphysics trace their view back to Carnap’s ‘Empiricism, Semantics and Ontology’. But the reason Carnap takes a dismissive attitude to metaphysics is a matter of controversy. I will argue that no reason is given in ‘Empiricism, Semantics and Ontology’, and this is because his reason for rejecting metaphysical debates was given in ‘Pseudo-Problems in Philosophy’. The argument there assumes verificationism, but I will argue that his argument survives the rejection of verificationism. The root (...)
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  19. added 2016-12-12
    Upping the Stakes and the Preface Paradox.Jonny Blamey - 2013 - In Frank Zenker (ed.), Bayesian Argumentation. Springer. pp. 195-210.
    Abstract The Preface Paradox, first introduced by David Makinson (1961), presents a plausible scenario where an agent is evidentially certain of each of a set of propositions without being evidentially certain of the conjunction of the set of propositions. Given reasonable assumptions about the nature of evidential certainty, this appears to be a straightforward contradiction. We solve the paradox by appeal to stake size sensitivity, which is the claim that evidential probability is sensitive to stake size. The argument is that (...)
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  20. added 2016-12-12
    Where Do Bayesian Priors Come From?Patrick Suppes - 2007 - Synthese 156 (3):441-471.
    Bayesian prior probabilities have an important place in probabilistic and statistical methods. In spite of this fact, the analysis of where these priors come from and how they are formed has received little attention. It is reasonable to excuse the lack, in the foundational literature, of detailed psychological theory of what are the mechanisms by which prior probabilities are formed. But it is less excusable that there is an almost total absence of a detailed discussion of the highly differentiating nature (...)
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  21. added 2016-12-08
    The Concept of Inductive Probability.Patrick Maher - 2006 - Erkenntnis 65 (2):185-206.
    The word ‘probability’ in ordinary language has two different senses, here called inductive and physical probability. This paper examines the concept of inductive probability. Attempts to express this concept in other words are shown to be either incorrect or else trivial. In particular, inductive probability is not the same as degree of belief. It is argued that inductive probabilities exist; subjectivist arguments to the contrary are rebutted. Finally, it is argued that inductive probability is an important concept and that it (...)
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  22. added 2016-12-08
    Logical Foundations of Evidential Support.Branden Fitelson - 2006 - Philosophy of Science 73 (5):500-512.
    Carnap's inductive logic (or confirmation) project is revisited from an "increase in firmness" (or probabilistic relevance) point of view. It is argued that Carnap's main desiderata can be satisfied in this setting, without the need for a theory of "logical probability." The emphasis here will be on explaining how Carnap's epistemological desiderata for inductive logic will need to be modified in this new setting. The key move is to abandon Carnap's goal of bridging confirmation and credence, in favor of bridging (...)
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  23. added 2016-12-08
    Problems with Priors in Probabilistic Measures of Coherence.David H. Glass - 2005 - Erkenntnis 63 (3):375-385.
    Two of the probabilistic measures of coherence discussed in this paper take probabilistic dependence into account and so depend on prior probabilities in a fundamental way. An example is given which suggests that this prior-dependence can lead to potential problems. Another coherence measure is shown to be independent of prior probabilities in a clearly defined sense and consequently is able to avoid such problems. The issue of prior-dependence is linked to the fact that the first two measures can be understood (...)
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  24. added 2016-12-08
    AIC and Large Samples.I. A. Kieseppä - 2003 - Philosophy of Science 70 (5):1265-1276.
    I discuss the behavior of the Akaike Information Criterion in the limit when the sample size grows. I show the falsity of the claim made recently by Stanley Mulaik in Philosophy of Science that AIC would not distinguish between saturated and other correct factor analytic models in this limit. I explain the meaning and demonstrate the validity of the familiar, more moderate criticism that AIC is not a consistent estimator of the number of parameters of the smallest correct model. I (...)
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  25. added 2016-12-08
    Scientific Reasoning: The Bayesian Approach.Peter Urbach & Colin Howson - 1993 - Open Court.
    Scientific reasoning is—and ought to be—conducted in accordance with the axioms of probability. This Bayesian view—so called because of the central role it accords to a theorem first proved by Thomas Bayes in the late eighteenth ...
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  26. added 2016-12-05
    Deceptive Updating and Minimal Information Methods.Haim Gaifman & Anubav Vasudevan - 2012 - Synthese 187 (1):147-178.
    The technique of minimizing information (infomin) has been commonly employed as a general method for both choosing and updating a subjective probability function. We argue that, in a wide class of cases, the use of infomin methods fails to cohere with our standard conception of rational degrees of belief. We introduce the notion of a deceptive updating method and argue that non-deceptiveness is a necessary condition for rational coherence. Infomin has been criticized on the grounds that there are no higher (...)
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  27. added 2016-12-02
    Connecting Applied and Theoretical Bayesian Epistemology: Data Relevance, Pragmatics, and the Legal Case of Sally Clark.Matthew J. Barker - 2016 - Journal of Applied Philosophy 33 (3).
    In this article applied and theoretical epistemologies benefit each other in a study of the British legal case of R. vs. Clark. Clark's first infant died at 11 weeks of age, in December 1996. About a year later, Clark had a second child. After that child died at eight weeks of age, Clark was tried for murdering both infants. Statisticians and philosophers have disputed how to apply Bayesian analyses to this case, and thereby arrived at different judgments about it. By (...)
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  28. added 2016-08-30
    The Semimeasure Property of Algorithmic Probability -- “Feature‘ or “Bug‘?Douglas Campbell - 2013 - In David L. Dowe (ed.), Algorithmic Probability and Friends: Bayesian Prediction and Artificial Intelligence. Springer Berlin Heidelberg. pp. 79--90.
    An unknown process is generating a sequence of symbols, drawn from an alphabet, A. Given an initial segment of the sequence, how can one predict the next symbol? Ray Solomonoff’s theory of inductive reasoning rests on the idea that a useful estimate of a sequence’s true probability of being outputted by the unknown process is provided by its algorithmic probability (its probability of being outputted by a species of probabilistic Turing machine). However algorithmic probability is a “semimeasure”: i.e., the sum, (...)
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  29. added 2016-08-01
    Ur-Priors, Conditionalization, and Ur-Prior Conditionalization.Christopher J. G. Meacham - 2016 - Ergo: An Open Access Journal of Philosophy 3.
    Conditionalization is a widely endorsed rule for updating one’s beliefs. But a sea of complaints have been raised about it, including worries regarding how the rule handles error correction, changing desiderata of theory choice, evidence loss, self-locating beliefs, learning about new theories, and confirmation. In light of such worries, a number of authors have suggested replacing Conditionalization with a different rule — one that appeals to what I’ll call “ur-priors”. But different authors have understood the rule in different ways, and (...)
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  30. added 2016-04-10
    On the a Priori and a Posteriori Assessment of Probabilities.Anubav Vasudevan - 2013 - Journal of Applied Logic 11 (4):440-451.
    We argue that in spite of their apparent dissimilarity, the methodologies employed in the a priori and a posteriori assessment of probabilities can both be justified by appeal to a single principle of inductive reasoning, viz., the principle of symmetry. The difference between these two methodologies consists in the way in which information about the single-trial probabilities in a repeatable chance process is extracted from the constraints imposed by this principle. In the case of a posteriori reasoning, these constraints inform (...)
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  31. added 2016-03-16
    Locating IBE in the Bayesian Framework.Jonathan Weisberg - 2009 - Synthese 167 (1):125-143.
    Inference to the Best Explanation (IBE) and Bayesianism are our two most prominent theories of scientific inference. Are they compatible? Van Fraassen famously argued that they are not, concluding that IBE must be wrong since Bayesianism is right. Writers since then, from both the Bayesian and explanationist camps, have usually considered van Fraassen’s argument to be misguided, and have plumped for the view that Bayesianism and IBE are actually compatible. I argue that van Fraassen’s argument is actually not so misguided, (...)
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  32. added 2016-01-26
    Defusing Bertrand's Paradox.Zalán Gyenis & Rédei Miklós - unknown
    The classical interpretation of probability together with the Principle of Indifference are formulated in terms of probability measure spaces in which the probability is given by the Haar measure. A notion called Labeling Irrelevance is defined in the category of Haar probability spaces, it is shown that Labeling Irrelevance is violated and Bertrand's Paradox is interpreted as the very proof of violation of Labeling Invariance. It is shown that Bangu's attempt to block the emergence of Bertrand's Paradox by requiring the (...)
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  33. added 2016-01-25
    Wittgenstein on Prior Probabilities.Michael E. Cuffaro - 2010 - Proceedings of the Canadian Society for History and Philosophy of Mathematics 23:85-98.
    Wittgenstein did not write very much on the topic of probability. The little we have comes from a few short pages of the Tractatus, some 'remarks' from the 1930s, and the informal conversations which went on during that decade with the Vienna Circle. Nevertheless, Wittgenstein's views were highly influential in the later development of the logical theory of probability. This paper will attempt to clarify and defend Wittgenstein's conception of probability against some oft-cited criticisms that stem from a misunderstanding of (...)
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  34. added 2016-01-25
    A Problem for Popper : Corroboration and the Logical Interpretation of Probability.Darrell Patrick Rowbottom - unknown
    How are we to understand the use of probability in Popper’s corroboration function? Popper says logically, but this raises a problem that becomes apparent when his views on logical probability are compared with those of Keynes. Specifically, Popper does not make it clear how we could have access to, or even calculate, probability values in a logical sense. For first, he would likely want to deny the Keynesian distinction between primary and secondary propositions, and the underlying notion of knowledge-by-acquaintance with (...)
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  35. added 2016-01-25
    Inductivism and Probabilism.Roger Rosenkrantz - 1971 - Synthese 23 (2-3):167 - 205.
    I I set out my view that all inference is essentially deductive and pinpoint what I take to be the major shortcomings of the induction rule.II The import of data depends on the probability model of the experiment, a dependence ignored by the induction rule. Inductivists admit background knowledge must be taken into account but never spell out how this is to be done. As I see it, that is the problem of induction.III The induction rule, far from providing a (...)
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  36. added 2016-01-18
    Discussion of Bruno de Finetti's Paper 'Initial Probabilities: A Prerequisite for Any Valid Induction'.I. J. Good - 1969 - Synthese 20 (1):17 - 24.
  37. added 2016-01-15
    Self-Locating Priors and Cosmological Measures.Frank Arntzenius & Cian Dorr - 2017 - In Khalil Chamcham, John Barrow, Simon Saunders & Joe Silk (eds.), The Philosophy of Cosmology. Cambridge: Cambridge University Press. pp. 396-428.
    We develop a Bayesian framework for thinking about the way evidence about the here and now can bear on hypotheses about the qualitative character of the world as a whole, including hypotheses according to which the total population of the world is infinite. We show how this framework makes sense of the practice cosmologists have recently adopted in their reasoning about such hypotheses.
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  38. added 2015-12-01
    Inference to the Best Explanation and Prior Probabilities.David Erik Nelson - 1999 - Dissertation, Rutgers the State University of New Jersey - New Brunswick
    Arguments for both Scientific Realism and the Governing Law analysis of scientific law rely heavily on the epistemological principle 'inference to the best explanation' . The most devastating arguments against these views claim that IBE is irrational by the lights of Bayesian epistemology. These debates are marred, however, by the lack of any sympathetic attempt to formulate principles of IBE that are both consistent with Bayesianism and able to do the work required of them by Scientific Realists and proponents of (...)
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  39. added 2015-10-12
    A Decision-Theoretical View of Default Priors.Stephen G. Walker & Eduardo Gutiérrez-Peña - 2011 - Theory and Decision 70 (1):1-11.
    In this article, we outline a simple and intuitively appealing procedure to derive default priors. The main idea is to regard the choice of such a prior as a formal Bayesian decision problem. We also discuss Jeffreys prior and more generally the reference prior of Bernardo (J R Stat Soc B 41:113–147, 1979) from this standpoint.
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  40. added 2015-10-12
    'P, and I Have Absolutely No Justification for Believing That P': The Necessary Falsehood of Orthodox Bayesianism.John N. Williams & Alan Hajek - unknown
    Orthodox Bayesianism tells a story about the epistemic trajectory of an ideally rational agent. The agent begins with a ‘prior’ probability function; thereafter, it conditionalizes on its evidence as it comes in. Consider, then, such an agent at the very beginning of its trajectory. It is ideally rational, but completely ignorant of which world is actual. Call this agent ‘Superbaby’.1 Superbaby personifies the Bayesian story. We argue that it must believe ‘Moorish’ propositions of the form.
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  41. added 2015-10-12
    Probabilistic Learning Models.Peter M. Williams - 2001 - In David Corfield & Jon Williamson (eds.), Foundations of Bayesianism. Kluwer Academic Publishers. pp. 117--134.
  42. added 2015-09-30
    Bayesian Humility.Adam Elga - 2016 - Philosophy of Science 83 (3):305-323.
    Say that an agent is "epistemically humble" if she is less than certain that her opinions will converge to the truth, given an appropriate stream of evidence. Is such humility rationally permissible? According to the orgulity argument : the answer is "yes" but long-run convergence-to-the-truth theorems force Bayesians to answer "no." That argument has no force against Bayesians who reject countable additivity as a requirement of rationality. Such Bayesians are free to count even extreme humility as rationally permissible.
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  43. added 2015-08-26
    Uncommon Priors Require Origin Disputes.Robin Hanson - 2006 - Theory and Decision 61 (4):319-328.
    In standard belief models, priors are always common knowledge. This prevents such models from representing agents’ probabilistic beliefs about the origins of their priors. By embedding standard models in a larger standard model, however, pre-priors can describe such beliefs. When an agent’s prior and pre-prior are mutually consistent, he must believe that his prior would only have been different in situations where relevant event chances were different, but that variations in other agents’ priors are otherwise completely unrelated to which events (...)
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  44. added 2015-08-25
    Accuracy, Risk, and the Principle of Indifference.Richard G. Pettigrew - 2016 - Philosophy and Phenomenological Research 92 (1):35-59.
    In Bayesian epistemology, the problem of the priors is this: How should we set our credences (or degrees of belief) in the absence of evidence? That is, how should we set our prior or initial credences, the credences with which we begin our credal life? David Lewis liked to call an agent at the beginning of her credal journey a superbaby. The problem of the priors asks for the norms that govern these superbabies. -/- The Principle of Indifference gives a (...)
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  45. added 2015-08-01
    The Principle of Indifference and Inductive Scepticism.Robert Smithson - 2017 - British Journal for the Philosophy of Science 68 (1):253-272.
    Many theorists have proposed that we can use the principle of indifference to defeat the inductive sceptic. But any such theorist must confront the objection that different ways of applying the principle of indifference lead to incompatible probability assignments. Huemer offers the explanatory priority proviso as a strategy for overcoming this objection. With this proposal, Huemer claims that we can defend induction in a way that is not question-begging against the sceptic. But in this article, I argue that the opposite (...)
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  46. added 2015-03-30
    Description and the Problem of Priors.Jeffrey A. Barrett - 2014 - Erkenntnis 79 (6):1343-1353.
    Belief-revision models of knowledge describe how to update one’s degrees of belief associated with hypotheses as one considers new evidence, but they typically do not say how probabilities become associated with meaningful hypotheses in the first place. Here we consider a variety of Skyrms–Lewis signaling game (Lewis in Convention. Harvard University Press, Cambridge, 1969; Skyrms in Signals evolution, learning, & information. Oxford University Press, New York, 2010) where simple descriptive language and predictive practice and associated basic expectations coevolve. Rather than (...)
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  47. added 2015-03-30
    The Incoherence of Agreeing to Disagree.Robert F. Nau - 1995 - Theory and Decision 39 (3):219-239.
  48. added 2015-03-30
    Subjective Probability Revision and Subsequent Decisions.Lee R. Beach & James A. Wise - 1969 - Journal of Experimental Psychology 81 (3):561.
  49. added 2015-01-30
    Reasonable Doubt : Uncertainty in Education, Science and Law.Tony Gardner-Medwin - 2011 - In Philip Dawid, William Twining & Mimi Vasilaki (eds.), Evidence, Inference and Enquiry. Oup/British Academy. pp. 465-483.
    The use of evidence to resolve uncertainties is key to many endeavours, most conspicuously science and law. Despite this, the logic of uncertainty is seldom taught explicitly, and often seems misunderstood. Traditional educational practice even fails to encourage students to identify uncertainty when they express knowledge, though mark schemes that reward the identification of reliable and uncertain responses have long been shown to encourage more insightful understanding. In our information-rich society the ability to identify uncertainty is often more important than (...)
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  50. added 2015-01-26
    Accardi on Quantum Theory and the "Fifth Axiom" of Probability.Hans Van Den Berg, Dick Hoekzema & Hans Radder - 1990 - Philosophy of Science 57 (1):149-157.
    In this paper we investigate Accardi's claim that the "quantum paradoxes" have their roots in probability theory and that, in particular, they can be evaded by giving up Bayes' rule, concerning the relation between composite and conditional probabilities. We reach the conclusion that, although it may be possible to give up Bayes' rule and define conditional probabilities differently, this contributes nothing to solving the philosophical problems which surround quantum mechanics.
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