Search results for 'Conditional probability' (try it on Scholar)

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  1. Rani Lill Anjum, Johan Arnt Myrstad & Stephen Mumford, Conditional Probability From an Ontological Point of View.score: 90.0
    This paper argues that the technical notion of conditional probability, as given by the ratio analysis, is unsuitable for dealing with our pretheoretical and intuitive understanding of both conditionality and probability. This is an ontological account of conditionals that include an irreducible dispositional connection between the antecedent and consequent conditions and where the conditional has to be treated as an indivisible whole rather than compositional. The relevant type of conditionality is found in some well-defined group of (...)
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  2. Donald Bamber (2000). Entailment with Near Surety of Scaled Assertions of High Conditional Probability. Journal of Philosophical Logic 29 (1):1-74.score: 90.0
    An assertion of high conditional probability or, more briefly, an HCP assertion is a statement of the type: The conditional probability of B given A is close to one. The goal of this paper is to construct logics of HCP assertions whose conclusions are highly likely to be correct rather than certain to be correct. Such logics would allow useful conclusions to be drawn when the premises are not strong enough to allow conclusions to be reached (...)
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  3. Horacio Arló Costa & Rohit Parikh (2005). Conditional Probability and Defeasible Inference. Journal of Philosophical Logic 34 (1):97 - 119.score: 90.0
    We offer a probabilistic model of rational consequence relations (Lehmann and Magidor, 1990) by appealing to the extension of the classical Ramsey-Adams test proposed by Vann McGee in (McGee, 1994). Previous and influential models of nonmonotonic consequence relations have been produced in terms of the dynamics of expectations (Gärdenfors and Makinson, 1994; Gärdenfors, 1993).'Expectation' is a term of art in these models, which should not be confused with the notion of expected utility. The expectations of an agent are some form (...)
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  4. Georg J. W. Dorn (1992/93). Popper’s Laws of the Excess of the Probability of the Conditional Over the Conditional Probability. Conceptus 26:3–61.score: 90.0
    Karl Popper discovered in 1938 that the unconditional probability of a conditional of the form ‘If A, then B’ normally exceeds the conditional probability of B given A, provided that ‘If A, then B’ is taken to mean the same as ‘Not (A and not B)’. So it was clear (but presumably only to him at that time) that the conditional probability of B given A cannot be reduced to the unconditional probability of (...)
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  5. Franco Montagna (2012). Partially Undetermined Many-Valued Events and Their Conditional Probability. Journal of Philosophical Logic 41 (3):563-593.score: 90.0
    A logic for classical conditional events was investigated by Dubois and Prade. In their approach, the truth value of a conditional event may be undetermined. In this paper we extend the treatment to many-valued events. Then we support the thesis that probability over partially undetermined events is a conditional probability, and we interpret it in terms of bets in the style of de Finetti. Finally, we show that the whole investigation can be carried out in (...)
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  6. Isabel Guerra Bobo (2013). On Quantum Conditional Probability. Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 28 (1):115-137.score: 90.0
    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 (...)
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  7. David Makinson (2011). Conditional Probability in the Light of Qualitative Belief Change. Journal of Philosophical Logic 40 (2):121 - 153.score: 90.0
    We explore ways in which purely qualitative belief change in the AGM tradition throws light on options in the treatment of conditional probability. First, by helping see why it can be useful to go beyond the ratio rule defining conditional from one-place probability. Second, by clarifying what is at stake in different ways of doing that. Third, by suggesting novel forms of conditional probability corresponding to familiar variants of qualitative belief change, and conversely. Likewise, (...)
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  8. Rohit Parikh (2005). Conditional Probability and Defeasible Inference. Journal of Philosophical Logic 34 (1):97 - 119.score: 90.0
    We offer a probabilistic model of rational consequence relations (Lehmann and Magidor, 1990) by appealing to the extension of the classical Ramsey-Adams test proposed by Vann McGee in (McGee, 1994). Previous and influential models of nonmonotonic consequence relations have been produced in terms of the dynamics of expectations (Gärdenfors and Makinson, 1994; Gärdenfors, 1993).'Expectation' is a term of art in these models, which should not be confused with the notion of expected utility. The expectations of an agent are some form (...)
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  9. Tommaso Flaminio (2007). NP-Containment for the Coherence Test of Assessments of Conditional Probability: A Fuzzy Logical Approach. [REVIEW] Archive for Mathematical Logic 46 (3-4):301-319.score: 90.0
    In this paper we investigate the problem of testing the coherence of an assessment of conditional probability following a purely logical setting. In particular we will prove that the coherence of an assessment of conditional probability χ can be characterized by means of the logical consistency of a suitable theory T χ defined on the modal-fuzzy logic FP k (RŁΔ) built up over the many-valued logic RŁΔ. Such modal-fuzzy logic was previously introduced in Flaminio (Lecture Notes (...)
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  10. Allen Stairs & Jeffrey Bub (2006). Local Realism and Conditional Probability. Foundations of Physics 36 (4):585-601.score: 75.0
    Emilio Santos has argued (Santos, Studies in History and Philosophy of Physics http: //arxiv-org/abs/quant-ph/0410193) that to date, no experiment has provided a loophole-free refutation of Bell’s inequalities. He believes that this provides strong evidence for the principle of local realism, and argues that we should reject this principle only if we have extremely strong evidence. However, recent work by Malley and Fine (Non-commuting observables and local realism, http: //arxiv-org/abs/quant-ph/0505016) appears to suggest that experiments refuting Bell’s inequalities could at most confirm (...)
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  11. Norman H. Anderson (1960). Effect of First-Order Conditional Probability in a Two-Choice Learning Situation. Journal of Experimental Psychology 59 (2):73.score: 75.0
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  12. Tommaso Flaminio & Franco Montagna (2005). A Logical and Algebraic Treatment of Conditional Probability. Archive for Mathematical Logic 44 (2):245-262.score: 75.0
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  13. Daniel Rothschild, Capturing the Relationship Between Conditionals and Conditional Probability with a Trivalent Semantics.score: 74.0
    Explains how to use a trivalent semantics to explain what is often called Adam’s Thesis, the thesis that the probability of a conditional is the conditional probability of the consequent given the antecedent.
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  14. Alexandre Street (2010). On the Conditional Value-at-Risk Probability-Dependent Utility Function. Theory and Decision 68 (1-2):49-68.score: 72.0
    The Expected Shortfall or Conditional Value-at-Risk (CVaR) has been playing the role of main risk measure in the recent years and paving the way for an enormous number of applications in risk management due to its very intuitive form and important coherence properties. This work aims to explore this measure as a probability-dependent utility functional, introducing an alternative view point for its Choquet Expected Utility representation. Within this point of view, its main preference properties will be characterized and (...)
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  15. Bryan Cort & Britt Anderson (2013). Conditional Probability Modulates Visual Search Efficiency. Frontiers in Human Neuroscience 7.score: 66.0
    We investigated the effects of probability on visual search. Previous work has shown that people can utilize spatial and sequential probability information to improve target detection. We hypothesized that performance improvements from probability information would extend to the efficiency of visual search. Our task was a simple visual search in which the target was always present among a field of distractors, and could take one of two colors. The absolute probability of the target being either color (...)
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  16. Alan Hájek (2003). What Conditional Probability Could Not Be. Synthese 137 (3):273--323.score: 60.0
    Kolmogorov''s axiomatization of probability includes the familiarratio formula for conditional probability: 0).$$ " align="middle" border="0">.
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  17. A. Millar & A. Haddock, Why the Conditional Probability Solution to the Swamping Problem Fails.score: 60.0
    The Swamping Problem is one of the standard objections to reliabilism. If one assumes, as reliabilism does, that truth is the only non instrumental epistemic value, then the worry is that the additional value of knowledge over true belief cannot be adequately explained, for reliability only has instrumental value relative to the non instrumental value of truth. Goldman and Olsson reply to this objection that reliabilist knowledge raises the objective probability of future true beliefs and is thus more valuable (...)
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  18. Frank Döring (2000). Conditional Probability and Dutch Books. Philosophy of Science 67 (3):391-409.score: 60.0
    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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  19. Joachim Horvath (2009). Why the Conditional Probability Solution to the Swamping Problem Fails. Grazer Philosophische Studien 79 (1):115-120.score: 60.0
    The Swamping Problem is one of the standard objections to reliabilism. If one assumes, as reliabilism does, that truth is the only non-instrumental epistemic value, then the worry is that the additional value of knowledge over true belief cannot be adequately explained, for reliability only has instrumental value relative to the non-instrumental value of truth. Goldman and Olsson reply to this objection that reliabilist knowledge raises the objective probability of future true beliefs and is thus more valuable than mere (...)
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  20. Charles G. Morgan (1999). Conditionals, Comparative Probability, and Triviality: The Conditional of Conditional Probability Cannot Be Represented in the Object Language. Topoi 18 (2):97-116.score: 60.0
    In this paper we examine the thesis that the probability of the conditional is the conditional probability. Previous work by a number of authors has shown that in standard numerical probability theories, the addition of the thesis leads to triviality. We introduce very weak, comparative conditional probability structures and discuss some extremely simple constraints. We show that even in such a minimal context, if one adds the thesis that the probability of a (...)
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  21. Eyvind Ohm & Valerie A. Thompson (2006). Conditional Probability and Pragmatic Conditionals: Dissociating Truth and Effectiveness. Thinking and Reasoning 12 (3):257 – 280.score: 60.0
    Recent research (e.g., Evans & Over, 2004) has provided support for the hypothesis that people evaluate the probability of conditional statements of the form if p then q as the conditional probability of q given p , P( q / p ). The present paper extends this approach to pragmatic conditionals in the form of inducements (i.e., promises and threats) and advice (i.e., tips and warnings). In so doing, we demonstrate a distinction between the truth status (...)
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  22. Teddy Seidenfeld, Remarks on the Theory of Conditional Probability: Some Issues of Finite Versus Countable Additivity.score: 60.0
    This paper (based on joint work with M.J.Schervish and J.B.Kadane) discusses some differences between the received theory of regular conditional distributions, which is the countably additive theory of conditional probability, and a rival theory of conditional probability using the theory of finitely additive probability. The focus of the paper is maximally "improper" conditional probability distributions, where the received theory requires, in effect, that P{a: P(a|a) = 0} = 1. This work builds upon (...)
     
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  23. Erik J. Olsson (2009). In Defense of the Conditional Probability Solution to the Swamping Problem. Grazer Philosophische Studien 79 (1):93-114.score: 60.0
    Knowledge is more valuable than mere true belief. Many authors contend, however, that reliabilism is incompatible with this item of common sense. If a belief is true, adding that it was reliably produced doesn't seem to make it more valuable. The value of reliability is swamped by the value of truth. In Goldman and Olsson (2009), two independent solutions to the problem were suggested. According to the conditional probability solution, reliabilist knowledge is more valuable in virtue of being (...)
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  24. Niki Pfeifer & G. D. Kleiter (2010). The Conditional in Mental Probability Logic. In M. Oaksford & N. Chater (eds.), Cognition and Conditionals: Probability and Logic in Human Thought. Oxford University Press. 153--173.score: 60.0
    The present chapter describes a probabilistic framework of human reasoning. It is based on probability logic. While there are several approaches to probability logic, we adopt the coherence based approach.
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  25. Niki Pfeifer & G. D. Kleiter (2006). Inference in Conditional Probability Logic. Kybernetika 42 (2):391--404.score: 60.0
    An important field of probability logic is the investigation of inference rules that propagate point probabilities or, more generally, interval probabilities from premises to conclusions. Conditional probability logic (CPL) interprets the common sense expressions of the form “if . . . , then . . . ” by conditional probabilities and not by the probability of the material implication. An inference rule is probabilistically informative if the coherent probability interval of its conclusion is not (...)
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  26. C. Martin Edwards & Gottfried T. Rüttimann (1990). On Conditional Probability in GL Spaces. Foundations of Physics 20 (7):859-872.score: 60.0
    We investigate the notion of conditional probability and the quantum mechanical concept of state reduction in the context of GL spaces satisfying the Alfsen-Shultz condition.
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  27. Vincent Corbin & Neil J. Cornish (2009). Semi-Classical Limit and Minimum Decoherence in the Conditional Probability Interpretation of Quantum Mechanics. Foundations of Physics 39 (5):474-485.score: 60.0
    The Conditional Probability Interpretation of Quantum Mechanics replaces the abstract notion of time used in standard Quantum Mechanics by the time that can be read off from a physical clock. The use of physical clocks leads to apparent non-unitary and decoherence. Here we show that a close approximation to standard Quantum Mechanics can be recovered from conditional Quantum Mechanics for semi-classical clocks, and we use these clocks to compute the minimum decoherence predicted by the Conditional (...) Interpretation. (shrink)
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  28. Giulianella Coletti, Angelo Gilio & Romano Scozzafava (1993). Comparative Probability for Conditional Events: A New Look Through Coherence. Theory and Decision 35 (3):237-258.score: 60.0
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  29. Frank Doring (2000). Conditional Probability and Dutch Books. Philosophy of Science 67 (3):391 - 409.score: 60.0
    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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  30. Laura Macchi & Maria Bagassi (2007). The Underinformative Formulation of Conditional Probability. Behavioral and Brain Sciences 30 (3):274-275.score: 60.0
    The formulation of the conditional probability in classical tasks does not guarantee the effective transmission of the independence of the hit rate from the base rate. In these kinds of tasks, data are all available, but subjects are able to understand them in the specific meanings proper to a specialized language only if these are adequately transmitted. From this perspective, the partitive formulation should not be considered a facilitation, but rather, a way of effectively transmitting the conditional (...)
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  31. James R. Erickson & Karen K. Block (1970). Conditional Response Distributions in a Multiple-Choice Probability-Learning Situtation. Journal of Experimental Psychology 86 (2):328.score: 60.0
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  32. Kenny Easwaran (2011). Varieties of Conditional Probability. In Prasanta Bandyopadhyay & Malcolm Forster (eds.), Handbook for Philosophy of Statistics. North Holland.score: 60.0
    I consider the notions of logical probability, degree of belief, and objective chance, and argue that a different formalism for conditional probability is appropriate for each.
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  33. Robert S. Witte (1961). Conditional Response Probability in a T Maze. Journal of Experimental Psychology 62 (5):439.score: 60.0
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  34. Horacio Arló-Costa & Richmond H. Thomason (2001). Iterative Probability Kinematics. Journal of Philosophical Logic 30 (5):479-524.score: 54.0
    Following the pioneer work of Bruno De Finetti [12], conditional probability spaces (allowing for conditioning with events of measure zero) have been studied since (at least) the 1950's. Perhaps the most salient axiomatizations are Karl Popper's in [31], and Alfred Renyi's in [33]. Nonstandard probability spaces [34] are a well know alternative to this approach. Vann McGee proposed in [30] a result relating both approaches by showing that the standard values of infinitesimal probability functions are representable (...)
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  35. Horacio Arlo-Costa & Richmond H. Thomason, Iterative Probability Kinematics.score: 54.0
    Following the pioneer work of Bruno De Finetti, conditional probability spaces (allowing for conditioning with events of measure zero) have been studied since (at least) the 1950's.
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  36. Johan van Benthem (2003). Conditional Probability Meets Update Logic. Journal of Logic, Language and Information 12 (4):409-421.score: 52.0
    Dynamic update of information states is a new paradigm in logicalsemantics. But such updates are also a traditional hallmark ofprobabilistic reasoning. This note brings the two perspectives togetherin an update mechanism for probabilities which modifies state spaces.
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  37. Richard Bradley (1999). Conditional Desirability. Theory and Decision 47 (1):23-55.score: 52.0
    Conditional attitudes are not the attitudes an agent is disposed to acquire in event of learning that a condition holds. Rather they are the components of agent's current attitudes that derive from the consideration they give to the possibility that the condition is true. Jeffrey's decision theory can be extended to include quantitative representation of the strength of these components. A conditional desirability measure for degrees of conditional desire is proposed and shown to imply that an agent's (...)
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  38. Alan Hájek (2003). Conditional Probability Is the Very Guide of Life. In Kyburg Jr, E. Henry & Mariam Thalos (eds.), Probability is the Very Guide of Life: The Philosophical Uses of Chance. Open Court. 183--203.score: 51.0
    in Probability is the Very Guide of Life: The Philosophical Uses of Chance, eds. Henry Kyburg, Jr. and Mariam Thalos, Open Court. Abridged version in Proceedings of the International Society for Bayesian Analysis 2002.
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  39. Igor Douven (2008). Kaufmann on the Probabilities of Conditionals. Journal of Philosophical Logic 37 (3):259 - 266.score: 51.0
    Kaufmann has recently argued that the thesis according to which the probability of an indicative conditional equals the conditional probability of the consequent given the antecedent under certain specifiable circumstances deviates from intuition. He presents a method for calculating the probability of a conditional that does seem to give the intuitively correct result under those circumstances. However, the present paper shows that Kaufmann’s method is inconsistent in that it may lead one to assign different (...)
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  40. Alan Hájek & N. Hall (1994). The Hypothesis of the Conditional Construitl of Conditional Probability. In Ellery Eells, Brian Skyrms & Ernest W. Adams (eds.), Probability and Conditionals: Belief Revision and Rational Decision. Cambridge University Press. 75.score: 51.0
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  41. Teddy Seidenfeld (2001). Remarks on the Theory of Conditional Probability: Some Issues of Finite Versus Countable Additivity. In Vincent F. Hendricks, Stig Andur Pederson & Klaus Frovin Jørgensen (eds.), Probability Theory: Philosophy, Recent History and Relations to Science. Synthese Library, Kluwer.score: 48.0
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  42. James Hawthorne (1998). On the Logic of Nonmonotonic Conditionals and Conditional Probabilities: Predicate Logic. [REVIEW] Journal of Philosophical Logic 27 (1):1-34.score: 48.0
    In a previous paper I described a range of nonmonotonic conditionals that behave like conditional probability functions at various levels of probabilistic support. These conditionals were defined as semantic relations on an object language for sentential logic. In this paper I extend the most prominent family of these conditionals to a language for predicate logic. My approach to quantifiers is closely related to Hartry Field's probabilistic semantics. Along the way I will show how Field's semantics differs from a (...)
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  43. Peter Milne (2008). Bets and Boundaries: Assigning Probabilities to Imprecisely Specified Events. Studia Logica 90 (3):425 - 453.score: 48.0
    Uncertainty and vagueness/imprecision are not the same: one can be certain about events described using vague predicates and about imprecisely specified events, just as one can be uncertain about precisely specified events. Exactly because of this, a question arises about how one ought to assign probabilities to imprecisely specified events in the case when no possible available evidence will eradicate the imprecision (because, say, of the limits of accuracy of a measuring device). Modelling imprecision by rough sets over an approximation (...)
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  44. Daniel Rothschild, Conditionals and Probability: A Classical Approach.score: 47.0
    Draft of a paper for the Sinn und Bedeutung 14 conference. Explains how to capture the link between conditionals the probability of indicative conditionals and conditional probability using a classical semantics for conditionals. (Note: some introductory material is shared with a twin paper, "Capturing the Relationship Between Conditionals and Conditional Probability with a Trivalent Semantics".).
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  45. Bas van Fraassen (1976). Probabilities of Conditionals. In C. Hooker (ed.), Foundations of probability theory, statistical inference, and statistical theories of science.score: 45.0
  46. Alan Hájek (2007). The Reference Class Problem is Your Problem Too. Synthese 156 (3):563--585.score: 45.0
    The reference class problem arises when we want to assign a probability to a proposition (or sentence, or event) X, which may be classified in various ways, yet its probability can change depending on how it is classified. The problem is usually regarded as one specifically for the frequentist interpretation of probability and is often considered fatal to it. I argue that versions of the classical, logical, propensity and subjectivist interpretations also fall prey to their own variants (...)
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  47. Alan Hájek (2012). The Fall of “Adams' Thesis”? Journal of Logic, Language and Information 21 (2):145-161.score: 45.0
    The so-called ‘Adams’ Thesis’ is often understood as the claim that the assertibility of an indicative conditional equals the corresponding conditional probability—schematically: $${({\rm AT})}\qquad\qquad\quad As(A\rightarrow B)=P({B|A}),{\rm provided}\quad P(A)\neq 0.$$ The Thesis is taken by many to be a touchstone of any theorizing about indicative conditionals. Yet it is unclear exactly what the Thesis is . I suggest some precise statements of it. I then rebut a number of arguments that have been given in its favor. Finally, I (...)
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  48. E. J. Lowe (2008). What is 'Conditional Probability'? Analysis 68 (299):218–223.score: 45.0
  49. Gerd Niestegge (2013). Three-Slit Experiments and Quantum Nonlocality. Foundations of Physics 43 (6):805-812.score: 45.0
    An interesting link between two very different physical aspects of quantum mechanics is revealed; these are the absence of third-order interference and Tsirelson’s bound for the nonlocal correlations. Considering multiple-slit experiments—not only the traditional configuration with two slits, but also configurations with three and more slits—Sorkin detected that third-order (and higher-order) interference is not possible in quantum mechanics. The EPR experiments show that quantum mechanics involves nonlocal correlations which are demonstrated in a violation of the Bell or CHSH inequality, but (...)
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  50. Horacio Arlo-Costa & Rohit Parikh, Conditional Probability and Defeasible Inference.score: 45.0
    Journal of Philosophical Logic 34, 97-119, 2005.
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