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  1. Brad Armendt (1980). Is There a Dutch Book Argument for Probability Kinematics? 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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  2. Frank Arntzenius (2003). Self-Locating Beliefs, Reflection, Conditionalization and Dutch Books. Journal of Philosophy 100:356-370.
  3. Frank Arntzenius (2003). Some Problems for Conditionalization and Reflection. Journal of Philosophy 100 (7):356-370.
  4. Feraz Azhar, Spectra of Conditionalization and Typicality in the Multiverse.
    An approach to testing theories describing a multiverse, that has gained interest of late, involves comparing theory-generated probability distributions over observables with their experimentally measured values. It is likely that such distributions, were we indeed able to calculate them unambiguously, will assign low probabilities to any such experimental measurements. An alternative to thereby rejecting these theories, is to conditionalize the distributions involved by restricting attention to domains of the multiverse in which we might arise. In order to elicit a crisp (...)
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  5. Feraz Azhar, Testing Typicality in Multiverse Cosmology.
    In extracting predictions from theories that describe a multiverse, we face the difficulty that we must assess probability distributions over possible observations, prescribed not just by an underlying theory, but by a theory together with a conditionalization scheme that allows for selection effects. This means we usually need to compare distributions that are consistent with a broad range of possible observations, with actual experimental data. One controversial means of making this comparison is by invoking the 'principle of mediocrity': that is, (...)
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  6. F. Bacchus, Mariam Thalos & H. E. Kyburg (1990). Against Conditionalization. Synthese 85 (3):475 - 506.
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  7. Fahiem Bacchus, Henry E. Kyburg Jr & Mariam Thalos (1990). Against Conditionalization. Synthese 85 (3):475 - 506.
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  8. Alexandru Baltag & Sonja Smets (2008). Probabilistic Dynamic Belief Revision. Synthese 165 (2):179 - 202.
    We investigate the discrete (finite) case of the Popper–Renyi theory of conditional probability, introducing discrete conditional probabilistic models for knowledge and conditional belief, and comparing them with the more standard plausibility models. We also consider a related notion, that of safe belief, which is a weak (non-negatively introspective) type of “knowledge”. We develop a probabilistic version of this concept (“degree of safety”) and we analyze its role in games. We completely axiomatize the logic of conditional belief, knowledge and safe belief (...)
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  9. Paul Bartha, How to Put Self-Locating Information in its Place.
    How can self-locating propositions be integrated into normal patterns of belief revision? Puzzles such as Sleeping Beauty seem to show that such propositions lead to violation of ordinary principles for reasoning with subjective probability, such as Conditionalization and Reflection. I show that sophisticated forms of Conditionalization and Reflection are not only compatible with self-locating propositions, but also indispensable in understanding how they can function as evidence in Sleeping Beauty and similar cases.
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  10. Paul Bartha & Christopher Hitchcock (1999). The Shooting-Room Paradox and Conditionalizing on Measurably Challenged Sets. Synthese 118 (3):403-437.
    We provide a solution to the well-known “Shooting-Room” paradox, developed by John Leslie in connection with his Doomsday Argument. In the “Shooting-Room” paradox, the death of an individual is contingent upon an event that has a 1/36 chance of occurring, yet the relative frequency of death in the relevant population is 0.9. There are two intuitively plausible arguments, one concluding that the appropriate subjective probability of death is 1/36, the other that this probability is 0.9. How are these two values (...)
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  11. Lee R. Beach & James A. Wise (1969). Subjective Probability Revision and Subsequent Decisions. Journal of Experimental Psychology 81 (3):561.
  12. Gordon Belot (forthcoming). Curve-Fitting for Bayesians? British Journal for the Philosophy of Science:axv061.
    Bayesians often assume, suppose, or conjecture that for any reasonable explication of the notion of simplicity a prior can be designed that will enforce a preference for hypotheses simpler in just that sense. Further, it is often claimed that the Bayesian framework automatically implements Occam’s razor—that conditionalizing on data consistent with both a simple theory and a complex theory more or less inevitably favours the simpler theory. But it is shown here that there are simplicity-driven approaches to curve-fitting problems that (...)
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  13. Johan van Benthem, Jelle Gerbrandy & Barteld Kooi (2009). Dynamic Update with Probabilities. Studia Logica 93 (1):67 - 96.
    Current dynamic-epistemic logics model different types of information change in multi-agent scenarios. We generalize these logics to a probabilistic setting, obtaining a calculus for multi-agent update with three natural slots: prior probability on states, occurrence probabilities in the relevant process taking place, and observation probabilities of events. To match this update mechanism, we present a complete dynamic logic of information change with a probabilistic character. The completeness proof follows a compositional methodology that applies to a much larger class of dynamic-probabilistic (...)
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  14. Isabel Guerra Bobo (2013). On Quantum Conditional Probability. Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 28 (1):115-137.
    We argue that quantum theory does not allow for a generalization of the notion of classical conditional probability by showing that the probability defined by the Lüders rule, standardly interpreted in the literature as the quantum-mechanical conditionalization rule, cannot be interpreted as such.Argumentamos que la teoría cuántica no admite una generalización de la noción clásica de probabilidad condicionada. Mostramos que la probabilidad definida por la regla de Lüders, interpretada generalmente como la regla de condicionalización mecánico-cuántica, no puede ser interpretada como (...)
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  15. Giacomo Bonanno (2005). A Simple Modal Logic for Belief Revision. Synthese 147 (2):193 - 228.
    We propose a modal logic based on three operators, representing intial beliefs, information and revised beliefs. Three simple axioms are used to provide a sound and complete axiomatization of the qualitative part of Bayes’ rule. Some theorems of this logic are derived concerning the interaction between current beliefs and future beliefs. Information flows and iterated revision are also discussed.
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  16. D. J. Bradley (2012). Four Problems About Self-Locating Belief. Philosophical Review 121 (2):149-177.
    This article defends the Doomsday Argument, the Halfer Position in Sleeping Beauty, the Fine-Tuning Argument, and the applicability of Bayesian confirmation theory to the Everett interpretation of quantum mechanics. It will argue that all four problems have the same structure, and it gives a unified treatment that uses simple models of the cases and no controversial assumptions about confirmation or self-locating evidence. The article will argue that the troublesome feature of all these cases is not self-location but selection effects.
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  17. Darren Bradley (2013). Dynamic Beliefs and the Passage of Time. In A. Capone & N. Feit (eds.), Attitudes De Se. University of Chicago
    How should our beliefs change over time? Much has been written about how our beliefs should change in the light of new evidence. But that is not the question I’m asking. Sometimes our beliefs change without new evidence. I previously believed it was Sunday. I now believe it’s Monday. In this paper I discuss the implications of such beliefs for philosophy of language. I will argue that we need to allow for ‘dynamic’ beliefs, that we need new norms of belief (...)
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  18. Darren Bradley (2011). Confirmation in a Branching World: The Everett Interpretation and Sleeping Beauty. British Journal for the Philosophy of Science 62 (2):323-342.
    Sometimes we learn what the world is like, and sometimes we learn where in the world we are. Are there any interesting differences between the two kinds of cases? The main aim of this article is to argue that learning where we are in the world brings into view the same kind of observation selection effects that operate when sampling from a population. I will first explain what observation selection effects are ( Section 1 ) and how they are relevant (...)
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  19. Darren Bradley (2011). Self-Location is No Problem for Conditionalization. Synthese 182 (3):393-411.
    How do temporal and eternal beliefs interact? I argue that acquiring a temporal belief should have no effect on eternal beliefs for an important range of cases. Thus, I oppose the popular view that new norms of belief change must be introduced for cases where the only change is the passing of time. I defend this position from the purported counter-examples of the Prisoner and Sleeping Beauty. I distinguish two importantly different ways in which temporal beliefs can be acquired and (...)
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  20. Darren Bradley (2010). Conditionalization and Belief De Se. 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. Darren Bradley (2007). Bayesianism And Self-Locating Beliefs. Dissertation, Stanford University
    How should we update our beliefs when we learn new evidence? Bayesian confirmation theory provides a widely accepted and well understood answer – we should conditionalize. But this theory has a problem with self-locating beliefs, beliefs that tell you where you are in the world, as opposed to what the world is like. To see the problem, consider your current belief that it is January. You might be absolutely, 100%, sure that it is January. But you will soon believe it (...)
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  22. Darren Bradley & Hannes Leitgeb (2006). When Betting Odds and Credences Come Apart: More Worries for Dutch Book Arguments. Analysis 66 (290):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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  23. Richard Bradley (2005). Radical Probabilism and Bayesian Conditioning. Philosophy of Science 72 (2):342-364.
    Richard Jeffrey espoused an antifoundationalist variant of Bayesian thinking that he termed ‘Radical Probabilism’. Radical Probabilism denies both the existence of an ideal, unbiased starting point for our attempts to learn about the world and the dogma of classical Bayesianism that the only justified change of belief is one based on the learning of certainties. Probabilistic judgment is basic and irreducible. Bayesian conditioning is appropriate when interaction with the environment yields new certainty of belief in some proposition but leaves one’s (...)
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  24. Richard Bradley (2005). Radical Probabilism and Bayesian Conditioning. Philosophy of Science 72 (2):342-364.
  25. Aaron Bronfman (2014). Conditionalization and Not Knowing That One Knows. Erkenntnis 79 (4):871-892.
    Bayesian Conditionalization is a widely used proposal for how to update one’s beliefs upon the receipt of new evidence. This is in part because of its attention to the totality of one’s evidence, which often includes facts about what one’s new evidence is and how one has come to have it. However, an increasingly popular position in epistemology holds that one may gain new evidence, construed as knowledge, without being in a position to know that one has gained this evidence. (...)
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  26. Peter M. Brown (1976). Conditionalization and Expected Utility. Philosophy of Science 43 (3):415-419.
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  27. Jeffrey Bub (1977). Von Neumann's Projection Postulate as a Probability Conditionalization Rule in Quantum Mechanics. Journal of Philosophical Logic 6 (1):381 - 390.
  28. Lara Buchak (2014). Learning Not to Be Naïve: A Comment on the Exchange Between Perrine/Wykstra and Draper. In Trent Dougherty & Justin McBrayer (eds.), Skeptical Theism: New Essays. Oxford University Press
    Does postulating skeptical theism undermine the claim that evil strongly confirms atheism over theism? According to Perrine and Wykstra, it does undermine the claim, because evil is no more likely on atheism than on skeptical theism. According to Draper, it does not undermine the claim, because evil is much more likely on atheism than on theism in general. I show that the probability facts alone do not resolve their disagreement, which ultimately rests on which updating procedure – conditionalizing or updating (...)
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  29. Jennifer Rose Carr (2016). Don’T Stop Believing. Canadian Journal of Philosophy 45 (5-6):744-766.
    It’s been argued that there are no diachronic norms of epistemic rationality. These arguments come partly in response to certain kinds of counterexamples to Conditionalization, but are mainly motivated by a form of internalism that appears to be in tension with any sort of diachronic coherence requirements. I argue that there are, in fact, fundamentally diachronic norms of rationality. And this is to reject at least a strong version of internalism. But I suggest a replacement for Conditionalization that salvages internalist (...)
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  30. David J. Chalmers (2014). Frontloading and Fregean Sense: Reply to Neta, Schroeter and Stanley. Analysis 74 (4):676-697.
  31. David Christensen (1992). Confirmational Holism and Bayesian Epistemology. Philosophy of Science 59 (4):540-557.
    Much contemporary epistemology is informed by a kind of confirmational holism, and a consequent rejection of the assumption that all confirmation rests on experiential certainties. Another prominent theme is that belief comes in degrees, and that rationality requires apportioning one's degrees of belief reasonably. Bayesian confirmation models based on Jeffrey Conditionalization attempt to bring together these two appealing strands. I argue, however, that these models cannot account for a certain aspect of confirmation that would be accounted for in any adequate (...)
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  32. Jeffrey Conditionalization (2013). Cognitive Penetration 12—16 (See Also 'Objections to Dogmatism and/or Phenomenal Conservatism'). In Chris Tucker (ed.), Seemings and Justification: New Essays on Dogmatism and Phenomenal Conservatism. OUP Usa 2--355.
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  33. H. A. Costa, J. Collins & I. Levi (1995). Desire-as-Belief Implies Opinionation or Indifference. Analysis 55 (1):2-5.
    The anti- Humean proposal of constructing desire as belief about what would be good must be abandoned on pain of triviality. Our central result shows that if an agent's belief- desire state is represented by Jeffrey's expected value theory enriched with the Desire as Belief Thesis (DAB), then, provided that three pairwise inconsistent propositions receive non- zero probability, the agent must view with indifference any proposition whose probability is greater than zero. Unlike previous results against DAB our Opinionation or Indifference (...)
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  34. Mikael Cozic (2011). Imagining and Sleeping Beauty: A Case for Double-Halfers. International Journal of Approximate Reasoning 52 (2):137-143.
    The aim of this paper is to provide a case for the double-halfer position in the sleeping beauty. This case relies on the use of the so-called imaging rule for probabilistic dynamics as a substitute for conditionalization. It is argued that the imaging rule is the appropriate one for dealing with belief change in sleeping beauty and that under natural assumptions, this rule results in the double-halfer position.
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  35. Eleonora Cresto (2010). Belief and Contextual Acceptance. Synthese 177 (1):41-66.
    I develop a strategy for representing epistemic states and epistemic changes that seeks to be sensitive to the difference between voluntary and involuntary aspects of our epistemic life, as well as to the role of pragmatic factors in epistemology. The model relies on a particular understanding of the distinction between full belief and acceptance , which makes room for the idea that our reasoning on both practical and theoretical matters typically proceeds in a contextual way. Within this framework, I discuss (...)
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  36. Persi Diaconis & Sandy L. Zabell (1982). Updating Subjective Probability. Journal of the American Statistical Association 77 (380):822-830.
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  37. M. Richard Diaz (1980). Deductive Completeness and Conditionalization in Systems of Weak Implication. Notre Dame Journal of Formal Logic 21 (1):119-130.
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  38. Franz Dietrich, Christian List & Richard Bradley, A Unified Characterization of Belief-Revision Rules.
    This paper characterizes several belief-revision rules in a unified framework: Bayesian revision upon learning some event, Jeffrey revision upon learning new probabilities of some events, Adams revision upon learning some new conditional probabilities, and 'dual-Jeffrey' revision upon learning a new conditional probability function. Despite their differences, these revision rules can be characterized in terms of the same two axioms: responsiveness, which requires that revised beliefs incorporate what has been learnt, and conservativeness, which requires that beliefs on which the learnt input (...)
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  39. Zoltan Domotor (1980). Probability Kinematics and Representation of Belief Change. Philosophy of Science 47 (3):384-403.
    Bayesian, Jeffrey and Field conditionals are compared and it is shown why the last two cannot be reduced to the first. Maximum relative entropy is used in two kinds of justification of the Field conditional and the dispensability of entropy principles in general is discussed.
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  40. Zoltan Domotor, Mario Zanotti & Henson Graves (1980). Probability Kinematics. Synthese 44 (3):421 - 442.
    Probability kinematics is studied in detail within the framework of elementary probability theory. The merits and demerits of Jeffrey's and Field's models are discussed. In particular, the principle of maximum relative entropy and other principles are used in an epistemic justification of generalized conditionals. A representation of conditionals in terms of Bayesian conditionals is worked out in the framework of external kinematics.
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  41. Frank Doring (2000). Conditional Probability and Dutch Books. Philosophy of Science 67 (3):391 - 409.
    There is no set Δ of probability axioms that meets the following three desiderata: (1) Δ is vindicated by a Dutch book theorem; (2) Δ does not imply regularity (and thus allows, among other things, updating by conditionalization); (3) Δ constrains the conditional probability q(·,z) even when the unconditional probability p(z) (=q(z,T)) equals 0. This has significant consequences for Bayesian epistemology, some of which are discussed.
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  42. Frank Doring (1999). Why Bayesian Psychology Is Incomplete. Philosophy of Science 66 (S1):S379 - S389.
    Bayesian psychology, in what is perhaps its most familiar version, is incomplete: Jeffrey conditionalization is not a complete account of rational belief change. Jeffrey conditionalization is sensitive to the order in which the evidence arrives. This order effect can be so pronounced as to call for a belief adjustment that cannot be understood as an assimilation of incoming evidence by Jeffrey's rule. Hartry Field's reparameterization of Jeffrey's rule avoids the order effect but fails as an account of how new evidence (...)
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  43. Frank Döring (1999). Why Bayesian Psychology is Incomplete. Philosophy of Science 66 (3):389.
    Bayesian psychology, in what is perhaps its most familiar version, is incomplete: Jeffrey conditionalization is not a complete account of rational belief change. Jeffrey conditionalization is sensitive to the order in which the evidence arrives. This order effect can be so pronounced as to call for a belief adjustment that cannot be understood as an assimilation of incoming evidence by Jeffrey's rule. Hartry Field's reparameterization of Jeffrey's rule avoids the order effect but fails as an account of how new evidence (...)
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  44. Jon Dorling (1992). Bayesian Conditionalization Resolves Positivist/Realist Disputes. Journal of Philosophy 89 (7):362-382.
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  45. I. Douven (2012). The Sequential Lottery Paradox. Analysis 72 (1):55-57.
    The Lottery Paradox is generally thought to point at a conflict between two intuitive principles, to wit, that high probability is sufficient for rational acceptability, and that rational acceptability is closed under logical derivability. Gilbert Harman has offered a solution to the Lottery Paradox that allows one to stick to both of these principles. The solution requires the principle that acceptance licenses conditionalization. The present study shows that adopting this principle alongside the principle that high probability is sufficient for rational (...)
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  46. Igor Douven (1999). Inference to the Best Explanation Made Coherent. Philosophy of Science 66 (Supplement):S424-S435.
    Van Fraassen (1989) argues that Inference to the Best Explanation is incoherent in the sense that adopting it as a rule for belief change will make one susceptible to a dynamic Dutch book. The present paper argues against this. A strategy is described that allows us to infer to the best explanation free of charge.
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  47. Igor Douven & Jonah N. Schupbach (2015). Probabilistic Alternatives to Bayesianism: The Case of Explanationism. Frontiers in Psychology 6 (459).
    There has been a probabilistic turn in contemporary cognitive science. Far and away, most of the work in this vein is Bayesian, at least in name. Coinciding with this development, philosophers have increasingly promoted Bayesianism as the best normative account of how humans ought to reason. In this paper, we make a push for exploring the probabilistic terrain outside of Bayesianism. Non-Bayesian, but still probabilistic, theories provide plausible competitors both to descriptive and normative Bayesian accounts. We argue for this general (...)
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  48. Igor Douven & Jonah N. Schupbach (2015). The Role of Explanatory Considerations in Updating. Cognition 142:299-311.
    There is an ongoing controversy in philosophy about the connection between explanation and inference. According to Bayesians, explanatory considerations should be given weight in determining which inferences to make, if at all, only insofar as doing so is compatible with Strict Conditionalization. Explanationists, on the other hand, hold that explanatory considerations can be relevant to the question of how much confidence to invest in our hypotheses in ways which violate Strict Conditionalization. The controversy has focused on normative issues. This paper (...)
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  49. Kai Draper (2013). The Evidential Relevance of Self-Locating Information. Philosophical Studies 166 (1):185-202.
    Philosophical interest in the role of self-locating information in the confirmation of hypotheses has intensified in virtue of the Sleeping Beauty problem. If the correct solution to that problem is 1/3, various attractive views on confirmation and probabilistic reasoning appear to be undermined; and some writers have used the problem as a basis for rejecting some of those views. My interest here is in two such views. One of them is the thesis that self-locating information cannot be evidentially relevant to (...)
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  50. Kai Draper (2010). Evidence Without Priors. Philo 13 (1):18-22.
    I argue that it is possible to acquire evidence that has no probability, not even zero, prior to its acquisition. If I am right then, contrary to certain Bayesian models of confirmation, conditionalization is not the only possible basis upon which a rational agent will alter her credence in some hypothesis in response to new evidence. My conclusion follows from certain analyses of the Sleeping Beauty problem. Because those analyses are controversial, however, I alter the Sleeping Beauty scenario to generate (...)
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