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Alan Hájek (2008). Interpretations of Probability.

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  1.  45
    Subjective Probability and its Dynamics.Alan Hajek & Julia Staffel - forthcoming - In Markus Knauff & Wolfgang Spohn (eds.), MIT Handbook of Rationality. MIT Press.
    This chapter is a philosophical survey of some leading approaches in formal epistemology in the so-called ‘Bayesian’ tradition. According to them, a rational agent’s degrees of belief—credences—at a time are representable with probability functions. We also canvas various further putative ‘synchronic’ rationality norms on credences. We then consider ‘diachronic’ norms that are thought to constrain how credences should respond to evidence. We discuss some of the main lines of recent debate, and conclude with some prospects for future research.
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  2.  32
    On Individual Risk.Philip Dawid - 2017 - Synthese 194 (9):3445-3474.
    We survey a variety of possible explications of the term “Individual Risk.” These in turn are based on a variety of interpretations of “Probability,” including classical, enumerative, frequency, formal, metaphysical, personal, propensity, chance and logical conceptions of probability, which we review and compare. We distinguish between “groupist” and “individualist” understandings of probability, and explore both “group to individual” and “individual to group” approaches to characterising individual risk. Although in the end that concept remains subtle and elusive, some pragmatic suggestions for (...)
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  3.  28
    Probabilistic Promotion Revisited.Jeff Behrends & Joshua DiPaolo - 2016 - Philosophical Studies 173 (7):1735-1754.
    Promotion is the relation between an act and a desire that obtains when the act advances or serves the desire. Under what conditions does an act promote a desire? Probabilistic accounts of promotion, the most prominent accounts, analyze promotion in terms of an increase in the probability of the desire’s satisfaction. In this paper, we clarify the promotion relation and explain why probabilistic accounts are attractive. Then we identify two questions probabilistic accounts must answer: the Baseline Question and the Interpretation (...)
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  4.  16
    A Humean Guide to Spielraum Probabilities.Claus Beisbart - 2016 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 47 (1):189-216.
    The most promising accounts of ontic probability include the Spielraum conception of probabilities, which can be traced back to J. von Kries and H. Poincaré, and the best system account by D. Lewis. This paper aims at comparing both accounts and at combining them to obtain the best of both worlds. The extensions of both Spielraum and best system probabilities do not coincide because the former only apply to systems with a special dynamics. Conversely, Spielraum probabilities may not be part (...)
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  5.  25
    Laplaceanism Defended.Peter Gildenhuys - 2016 - Biology and Philosophy 31 (3):395-408.
    This work is a critical consideration of several arguments recently given by Elliott Sober that are aimed at undermining the Laplacean stance on probability in evolutionary theory. The Laplacean contends that the only objective probability an event has is the one assigned to it by a complete description of the relevant microparticles. Sober alleges a formal demonstration that the Laplacean stance on probability in evolutionary theory is inconsistent. But Sober’s argument contains a crucial lacuna, one that likely cannot be repaired (...)
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  6.  41
    The Propensity Interpretation of Probability: A Re-Evaluation.Joseph Berkovitz - 2015 - Erkenntnis 80 (S3):629-711.
    Single-case and long-run propensity theories are among the main objective interpretations of probability. There have been various objections to these theories, e.g. that it is difficult to explain why propensities should satisfy the probability axioms and, worse, that propensities are at odds with these axioms, that the explication of propensities is circular and accordingly not informative, and that single-case propensities are metaphysical and accordingly non-scientific. We consider various propensity theories of probability and their prospects in light of these objections. We (...)
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  7.  13
    On Probabilities in Biology and Physics.Joseph Berkovitz & Philippe Huneman - 2015 - Erkenntnis 80 (S3):433-456.
    This volume focuses on various questions concerning the interpretation of probability and probabilistic reasoning in biology and physics. It is inspired by the idea that philosophers of biology and philosophers of physics who work on the foundations of their disciplines encounter similar questions and problems concerning the role and application of probability, and that interaction between the two communities will be both interesting and fruitful. In this introduction we present the background to the main questions that the volume focuses on (...)
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  8. Bayesian Confirmation: A Means with No End.Peter Brössel & Franz Huber - 2015 - British Journal for the Philosophy of Science 66 (4):737-749.
    Any theory of confirmation must answer the following question: what is the purpose of its conception of confirmation for scientific inquiry? In this article, we argue that no Bayesian conception of confirmation can be used for its primary intended purpose, which we take to be making a claim about how worthy of belief various hypotheses are. Then we consider a different use to which Bayesian confirmation might be put, namely, determining the epistemic value of experimental outcomes, and thus to decide (...)
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  9. Philosophy as Conceptual Engineering: Inductive Logic in Rudolf Carnap's Scientific Philosophy.Christopher F. French - 2015 - Dissertation, University of British Columbia
  10.  27
    Natural Probabilistic Information.Daniel Kraemer - 2015 - Synthese 192 (9):2901-2919.
    Natural information refers to the information carried by natural signs such as that smoke is thought to carry natural information about fire. A number of influential philosophers have argued that natural information can also be utilized in a theory of mental content. The most widely discussed account of natural information holds that it results from an extremely strong relation between sign and signified. Critics have responded that it is doubtful that there are many strong relations of this sort in the (...)
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  11. How to Resolve Doxastic Disagreement.Peter Brössel & Anna-Maria A. Eder - 2014 - Synthese 191 (11):2359-2381.
    How should an agent revise her epistemic state in the light of doxastic disagreement? The problems associated with answering this question arise under the assumption that an agent’s epistemic state is best represented by her degree of belief function alone. We argue that for modeling cases of doxastic disagreement an agent’s epistemic state is best represented by her confirmation commitments and the evidence available to her. Finally, we argue that given this position it is possible to provide an adequate answer (...)
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  12.  41
    Probability and Logic.Kenny Easwaran - 2014 - Philosophy Compass 9 (12):876-883.
    Probability and logic are two branches of mathematics that have important philosophical applications. This article discusses several areas of intersection between them. Several involve the role for probability in giving semantics for logic or the role of logic in governing assignments of probability. Some involve probability over non-classical logic or self-referential sentences.
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  13.  38
    Justification and Cognitive Algorithms.Luis Rosa - 2014 - Philosophia 42 (2):503-515.
    In this paper, we offer an alternative interpretation for the claim that ‘S is justified in believing that φ’. First, we present what seems to be a common way of interpreting this claim: as an attribution of propositional justification. According to this interpretation, being justified is just a matter of having confirming evidence. We present a type of case that does not fit well with the standard concept, where considerations about cognition are made relevant. The concept of cognitive algorithm is (...)
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  14.  94
    Collins' Core Fine-Tuning Argument.Mark Douglas Saward - 2014 - International Journal for Philosophy of Religion 76 (2):209-222.
    Collins (The Blackwell companion to natural theology, 2009) presents an argument he calls the ‘core fine-tuning argument’. In this paper, I show that Collins’ argument is flawed in at least two ways. First, the structure, depending on likelihoods, fails to establish anything about the posterior probability of God’s existence given fine-tuning. As an argument for God’s existence, this is a serious failing. Second, his analysis of what is appropriately restricted background knowledge, combined with the credences of a specially chosen ‘alien’, (...)
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  15.  74
    The Interference Problem for the Betting Interpretation of Degrees of Belief.Lina Eriksson & Wlodek Rabinowicz - 2013 - Synthese 190 (5):809-830.
    The paper’s target is the historically influential betting interpretation of subjective probabilities due to Ramsey and de Finetti. While there are several classical and well-known objections to this interpretation, the paper focuses on just one fundamental problem: There is a sense in which degrees of belief cannot be interpreted as betting rates. The reasons differ in different cases, but there’s one crucial feature that all these cases have in common: The agent’s degree of belief in a proposition A does not (...)
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  16.  38
    On Chance. [REVIEW]Joshua Luczak - 2013 - Metascience 22 (1):85-87.
  17.  33
    Trait Fitness is Not a Propensity, but Fitness Variation Is.Elliott Sober - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (3):336-341.
    The propensity interpretation of fitness draws on the propensity interpretation of probability, but advocates of the former have not attended sufficiently to problems with the latter. The causal power of C to bring about E is not well-represented by the conditional probability Pr. Since the viability fitness of trait T is the conditional probability Pr, the viability fitness of the trait does not represent the degree to which having the trait causally promotes surviving. The same point holds for fertility fitness. (...)
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  18.  44
    A Frequentist Interpretation of Probability for Model-Based Inductive Inference.Aris Spanos - 2013 - Synthese 190 (9):1555-1585.
    The main objective of the paper is to propose a frequentist interpretation of probability in the context of model-based induction, anchored on the Strong Law of Large Numbers (SLLN) and justifiable on empirical grounds. It is argued that the prevailing views in philosophy of science concerning induction and the frequentist interpretation of probability are unduly influenced by enumerative induction, and the von Mises rendering, both of which are at odds with frequentist model-based induction that dominates current practice. The differences between (...)
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  19. The New Tweety Puzzle: Arguments Against Monistic Bayesian Approaches in Epistemology and Cognitive Science.Matthias Unterhuber & Gerhard Schurz - 2013 - Synthese 190 (8):1407-1435.
    In this paper we discuss the new Tweety puzzle. The original Tweety puzzle was addressed by approaches in non-monotonic logic, which aim to adequately represent the Tweety case, namely that Tweety is a penguin and, thus, an exceptional bird, which cannot fly, although in general birds can fly. The new Tweety puzzle is intended as a challenge for probabilistic theories of epistemic states. In the first part of the paper we argue against monistic Bayesians, who assume that epistemic states can (...)
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  20.  59
    Mechanistic Probability.Marshall Abrams - 2012 - Synthese 187 (2):343-375.
    I describe a realist, ontologically objective interpretation of probability, "far-flung frequency (FFF) mechanistic probability". FFF mechanistic probability is defined in terms of facts about the causal structure of devices and certain sets of frequencies in the actual world. Though defined partly in terms of frequencies, FFF mechanistic probability avoids many drawbacks of well-known frequency theories and helps causally explain stable frequencies, which will usually be close to the values of mechanistic probabilities. I also argue that it's a virtue rather than (...)
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  21.  88
    Contradictory Information: Too Much of a Good Thing. [REVIEW]J. Michael Dunn - 2010 - Journal of Philosophical Logic 39 (4):425 - 452.
    Both I and Belnap, motivated the "Belnap-Dunn 4-valued Logic" by talk of the reasoner being simply "told true" (T) and simply "told false" (F), which leaves the options of being neither "told true" nor "told false" (N), and being both "told true" and "told false" (B). Belnap motivated these notions by consideration of unstructured databases that allow for negative information as well as positive information (even when they conflict). We now experience this on a daily basis with the Web. But (...)
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  22.  48
    Explication of Inductive Probability.Patrick Maher - 2010 - Journal of Philosophical Logic 39 (6):593 - 616.
    Inductive probability is the logical concept of probability in ordinary language. It is vague but it can be explicated by defining a clear and precise concept that can serve some of the same purposes. This paper presents a general method for doing such an explication and then a particular explication due to Carnap. Common criticisms of Carnap's inductive logic are examined; it is shown that most of them are spurious and the others are not fundamental.
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  23. Recursive Tracking Versus Process Reliabilism. [REVIEW]Alvin I. Goldman - 2009 - Philosophy and Phenomenological Research 79 (1):223-230.
    Sherrilyn Roush’s Tracking Truth (2005) is an impressive, precisioncrafted work. Although it sets out to rehabilitate the epistemological theory of Robert Nozick’s Philosophical Explanations (1981), its departures from Nozick’s line are extensive and original enough that it should be regarded as a distinct form of epistemological externalism. Roush’s mission is to develop an externalism that averts the problems and counterexamples encountered not only by Nozick’s theory but by other varieties of externalism as well. Roush advances both a theory of knowledge (...)
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  24.  60
    On Background: Using Two-Argument Chance.Kevin Nelson - 2009 - Synthese 166 (1):165-186.
    I follow Hájek (Synthese 137:273–323, 2003c) by taking objective probability to be a function of two propositional arguments—that is, I take conditional probability as primitive. Writing the objective probability of q given r as P(q, r), I argue that r may be chosen to provide less than a complete and exact description of the world’s history or of its state at any time. It follows that nontrivial objective probabilities are possible in deterministic worlds and about the past. A very simple (...)
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  25. The Role of Axioms in Mathematics.Kenny Easwaran - 2008 - Erkenntnis 68 (3):381-391.
    To answer the question of whether mathematics needs new axioms, it seems necessary to say what role axioms actually play in mathematics. A first guess is that they are inherently obvious statements that are used to guarantee the truth of theorems proved from them. However, this may neither be possible nor necessary, and it doesn’t seem to fit the historical facts. Instead, I argue that the role of axioms is to systematize uncontroversial facts that mathematicians can accept from a wide (...)
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  26.  66
    Safety, Risk Acceptability, and Morality.James A. E. Macpherson - 2008 - Science and Engineering Ethics 14 (3):377-390.
    The primary aim of this article is to develop and defend a conceptual analysis of safety. The article begins by considering two previous analyses of safety in terms of risk acceptability. It is argued that these analyses fail because the notion of risk acceptability is more subjective than safety, as risk acceptability takes into account potential benefits in a way that safety does not. A distinction is then made between two different kinds of safety—safety qua cause and safety qua recipient—and (...)
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  27.  54
    Infinite Populations and Counterfactual Frequencies in Evolutionary Theory.Marshall Abrams - 2006 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 37 (2):256-268.
    One finds intertwined with ideas at the core of evolutionary theory claims about frequencies in counterfactual and infinitely large populations of organisms, as well as in sets of populations of organisms. One also finds claims about frequencies in counterfactual and infinitely large populations—of events—at the core of an answer to a question concerning the foundations of evolutionary theory. The question is this: To what do the numerical probabilities found throughout evolutionary theory correspond? The answer in question says that evolutionary probabilities (...)
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  28.  35
    Probabilistic Models of Cognition: Where Next?Nick Chater, Joshua B. Tenenbaum & Alan Yuille - 2006 - Trends in Cognitive Sciences 10 (7):292-293.
  29.  74
    Probabilistic Models of Cognition: Conceptual Foundations.Nick Chater & Alan Yuille - 2006 - Trends in Cognitive Sciences 10 (7):287-291.
    Remarkable progress in the mathematics and computer science of probability has led to a revolution in the scope of probabilistic models. In particular, ‘sophisticated’ probabilistic methods apply to structured relational systems such as graphs and grammars, of immediate relevance to the cognitive sciences. This Special Issue outlines progress in this rapidly developing field, which provides a potentially unifying perspective across a wide range of domains and levels of explanation. Here, we introduce the historical and conceptual foundations of the approach, explore (...)
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