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  1. The Evidence Against Kronz.Peter Achinstein - 1992 - Philosophical Studies 67 (2):169-175.
  2. Confirmation Theory, Order, and Periodicity.Peter Achinstein - 1963 - Philosophy of Science 30 (1):17-35.
    This paper examines problems of order and periodicity which arise when the attempt is made to define a confirmation function for a language containing elementary number theory as applied to a universe in which the individuals are considered to be arranged in some fixed order. Certain plausible conditions of adequacy are stated for such a confirmation function. By the construction of certain types of predicates, it is proved, however, that these conditions of adequacy are violated by any confirmation function defined (...)
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  3. Variety and Analogy in Confirmation Theory.Peter Achinstein - 1963 - Philosophy of Science 30 (3):207-221.
    Confirmation theorists seek to define a function that will take into account the various factors relevant in determining the degree to which an hypothesis is confirmed by its evidence. Among confirmation theorists, only Rudolf Carnap has constructed a system which purports to consider factors in addition to the number of instances, viz. the variety manifested by the instances and the amount of analogy between the instances. It is the purpose of this paper to examine the problem which these additional factors (...)
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  4. Bayesian Modeling of Human Sequential Decision-Making on the Multi-Armed Bandit Problem.Daniel Acuna & Paul Schrater - 2008 - In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 100--200.
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  5. Lax Monitoring Versus Logical Intuition: The Determinants of Confidence in Conjunction Fallacy.Balazs Aczel, Aba Szollosi & Bence Bago - 2015 - Thinking and Reasoning 22 (1):99-117.
    ABSTRACTThe general assumption that people fail to notice discrepancy between their answer and the normative answer in the conjunction fallacy task has been challenged by the theory of Logical Intuition. This theory suggests that people can detect the conflict between the heuristic and normative answers even if they do not always manage to inhibit their intuitive choice. This theory gained support from the finding that people report lower levels of confidence in their choice after they commit the conjunction fallacy compared (...)
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  6. Probability and the Art of Judgement by Richard Jeffrey. [REVIEW]Ernest W. Adams - 1993 - Journal of Philosophy 90 (3):154-157.
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  7. Confirming Inexact Generalizations.Ernest W. Adams - 1988 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1988:10 - 16.
    I suppose that 'ravens are black' is an inexact generalization having a degree of truth measured by the proportion of ravens that are black, and a probability measured by its expected degree of truth in different 'possible worlds.' Given this, 'ravens are black' differs in truth, probability, and confirmation from 'non-black things are not ravens', and this suggests a new approach to Hempel's Paradox as well as to other aspects of confirmation. Basic concepts of a formal theory developing this approach (...)
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  8. If the Base Rate Fallacy is a Fallacy, Does It Matter How Frequently It is Committed?Jonathan E. Adler - 1997 - Behavioral and Brain Sciences 20 (4):774-775.
    In many base rate studies, a judgment is required for which the base rates are relevant, and subjects do not use them. It is inferred that the base rates are ignored; I question this inference. Second, I argue that the base rate fallacy is not less significant for what it reveals about human reasoning, if it occurs less frequently than has been alleged.
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  9. Hume and the Independent Witnesses.Arif Ahmed - 2015 - Mind 124 (496):1013-1044.
    The Humean argument concerning miracles says that one should always think it more likely that anyone who testifies to a miracle is lying or deluded than that the alleged miracle actually occurred, and so should always reject any single report of it. A longstanding and widely accepted objection is that even if this is right, the concurring and non-collusive testimony of many witnesses should make it rational to believe in whatever miracle they all report. I argue that on the contrary, (...)
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  10. In Defence of Objective Bayesianism.P. M. Ainsworth - 2012 - Analysis 72 (4):832-843.
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  11. Free or Ensnared? The Hidden Nets Of.Jean Aitchison - 1995 - In E. Barker (ed.), Lse on Freedom. Lse Books. pp. 75.
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  12. Evolutionary Psychology and Bayesian Modeling.Laith Al-Shawaf & David Buss - 2011 - Behavioral and Brain Sciences 34 (4):188-189.
    The target article provides important theoretical contributions to psychology and Bayesian modeling. Despite the article's excellent points, we suggest that it succumbs to a few misconceptions about evolutionary psychology (EP). These include a mischaracterization of evolutionary psychology's approach to optimality; failure to appreciate the centrality of mechanism in EP; and an incorrect depiction of hypothesis testing. An accurate characterization of EP offers more promise for successful integration with Bayesian modeling.
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  13. Trying to Resolve the Two-Envelope Problem.Casper J. Albers, Barteld P. Kooi & Willem Schaafsma - 2005 - Synthese 145 (1):89-109.
    After explaining the well-known two-envelope paradox by indicating the fallacy involved, we consider the two-envelope problem of evaluating the factual information provided to us in the form of the value contained by the envelope chosen first. We try to provide a synthesis of contributions from economy, psychology, logic, probability theory (in the form of Bayesian statistics), mathematical statistics (in the form of a decision-theoretic approach) and game theory. We conclude that the two-envelope problem does not allow a satisfactory solution. An (...)
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  14. Should Bayesians Bet Where Frequentists Fear to Tread?Max Albert - 2005 - Philosophy of Science 72 (4):584-593.
  15. Bayesian Rationality and Decision Making: A Critical Review.Max Albert - 2003 - Analyse & Kritik 25 (1):101-117.
    Bayesianism is the predominant philosophy of science in North-America, the most important school of statistics world-wide, and the general version of the rational-choice approach in the social sciences. Although often rejected as a theory of actual behavior, it is still the benchmark case of perfect rationality. The paper reviews the development of Bayesianism in philosophy, statistics and decision making and questions its status as an account of perfect rationality. Bayesians, who otherwise are squarely in the empiricist camp, invoke a priori (...)
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  16. The Stag Hunt and the Evolution of Social Structure, Brian Skyrms. Cambridge University Press, 2004, 149 Pages. [REVIEW]J. McKenzie Alexander - 2006 - Economics and Philosophy 22 (3):441-448.
  17. Nature, Science, Bayes 'Theorem, and the Whole of Reality‖.Moorad Alexanian - forthcoming - Zygon.
    A fundamental problem in science is how to make logical inferences from scientific data. Mere data does not suffice since additional information is necessary to select a domain of models or hypotheses and thus determine the likelihood of each model or hypothesis. Thomas Bayes’ Theorem relates the data and prior information to posterior probabilities associated with differing models or hypotheses and thus is useful in identifying the roles played by the known data and the assumed prior information when making inferences. (...)
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  18. A Critical Discussion Of The Compatibility Of Bayesianism And Inference To The Best Explanation.Mark Alfano - 2007 - Philosophical Writings 34 (1).
    In this paper I critique Peter Lipton’s attempt to deal with the threat of Bayesianism to the normative aspect of his project in Inference to the Best Explanation. I consider the five approaches Lipton proposes for reconciling the doxastic recommendations of Inference to the Best Explanation with BA’s: IBE gives a ‘boost’ to the posterior probability of particularly ‘lovely’ hypotheses after the Bayesian calculation is performed; IBE helps us to set the likelihood of evidence on a given hypothesis; IBE helps (...)
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  19. Causal Discounting and Conditional Reasoning in Children.Nilufa Ali, Anne Schlottman, Abigail Shaw, Nick Chater, & Oaksford & Mike - 2010 - In Mike Oaksford & Nick Chater (eds.), Cognition and Conditionals: Probability and Logic in Human Thinking. Oxford University Press.
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  20. Causal Discounting and Conditional Reasoning in Children.Nilufa Ali, Anne Schlottmann, Abigail Shaw, Nick Chater & Mike Oaksford - 2010 - In M. Oaksford & N. Chater (eds.), Cognition and Conditionals: Probability and Logic in Human Thought. Oxford University Press.
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  21. The So-Called Allais Paradox and Rational Decisions Under Uncertainty.Maurice Allais - 1979 - In Maurice Allais & Ole Hagen (eds.), Expected Utility Hypotheses and the Allais Paradox. D. Reidel.
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  22. Expected Utility Hypotheses and the Allais Paradox.Maurice Allais & Ole Hagen (eds.) - 1979 - D. Reidel.
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  23. Erratum To: Synthese Special Issue: Representing Philosophy.Colin Allen & Tony Beavers - 2011 - Synthese 183 (2):277-277.
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  24. Artificial Intelligence and the Evidentiary Process: The Challenges of Formalism and Computation. [REVIEW]Ronald J. Allen - 2001 - Artificial Intelligence and Law 9 (2-3):99-114.
    The tension between rule and judgment is well known with respect to the meaning of substantive legal commands. The same conflict is present in fact finding. The law penetrates to virtually all aspects of human affairs; irtually any interaction can generate a legal conflict. Accurate fact finding about such disputes is a necessary condition for the appropriate application of substantive legal commands. Without accuracy in fact finding, the law is unpredictable, and thus individuals cannot efficiently accommodate their affairs to its (...)
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  25. Bayesian Learning for Cooperation in Multi-Agent Systems.Mair Allen-Williams & Nicholas R. Jennings - 2009 - In L. Magnani (ed.), Computational Intelligence. pp. 321--360.
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  26. Bayes and Health Care Research.Peter Allmark - 2004 - Medicine, Health Care and Philosophy 7 (3):321-332.
    Bayes’ rule shows how one might rationally change one’s beliefs in the light of evidence. It is the foundation of a statistical method called Bayesianism. In health care research, Bayesianism has its advocates but the dominant statistical method is frequentism. There are at least two important philosophical differences between these methods. First, Bayesianism takes a subjectivist view of probability (i.e. that probability scores are statements of subjective belief, not objective fact) whilst frequentism takes an objectivist view. Second, Bayesianism is explicitly (...)
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  27. Approaching Color with Bayesian Algorithms.Sarah Allred - 2012 - In Gary Hatfield & Sarah Allred (eds.), Visual Experience: Sensation, Cognition, and Constancy. Oxford University Press. pp. 212.
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  28. Bayes's Theorem (Proceedings of the British Academy, Vol. 113), Edited by Richard Swinburne, Oxford University Press, 2002, 160 Pages. [REVIEW]Paul Anand - 2005 - Economics and Philosophy 21 (1):139-142.
  29. The Myth of Computational Level Theory and the Vacuity of Rational Analysis.Barton L. Anderson - 2011 - Behavioral and Brain Sciences 34 (4):189-190.
    I extend Jones & Love's (J&L's) critique of Bayesian models and evaluate the conceptual foundations on which they are built. I argue that: (1) the part of Bayesian models is scientifically trivial; (2) theory is a fiction that arises from an inappropriate programming metaphor; and (3) the real scientific problems lie outside Bayesian theorizing.
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  30. Effect of First-Order Conditional Probability in a Two-Choice Learning Situation.Norman H. Anderson - 1960 - Journal of Experimental Psychology 59 (2):73.
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  31. Mr. Kneale on Probability and Induction.F. J. Anscombe - 1951 - Mind 60 (239):299-309.
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  32. Bayesian Inference and Contractualist Justification on Interstate 95.Arthur Isak Applbaum - 2014 - In Andrew I. Cohen & Christopher H. Wellman (eds.), Contemporary Debates in Applied Ethics. Wiley-Blackwell. pp. 219.
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  33. The Doomsday Simulation Argument. Or Why Isn't the End Nigh, and You're Not Living in a Simulation.Mr István A. Aranyosi - manuscript
    According to the Carter-Leslie Doomsday Argument, we should assign a high probability to the hypothesis that the human species will go extinct very soon. The argument is based on the application of Bayes’s theo-rem and a certain indifference principle with respect to the temporal location of our observed birth rank within the totality of birth ranks of all humans who will ever have lived. According to Bostrom’s Simulation Argument, which appeals to a weaker indifference principle than the Doomsday Argument, at (...)
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  34. Bayesian Epistemology and Epistemic Conditionals: On the Status of the Export-Import Laws.Horacio Arló-Costa - 2001 - Journal of Philosophy 98 (11):555-593.
    Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use.
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  35. Bayesian Epistemology and Epistemic Conditionals.Horacio Arló-Costa - 2001 - Journal of Philosophy 98 (11):555-593.
    The notion of probability occupies a central role in contemporary epistemology and cognitive science. Nevertheless, the classical notion of probability is hard to reconcile with the central notions postulated by the epistemological tradition.
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  36. Bayesianism, Infinite Decisions, and Binding.Frank Arntzenius, Adam Elga & John Hawthorne - 2004 - Mind 113 (450):251 - 283.
    We pose and resolve several vexing decision theoretic puzzles. Some are variants of existing puzzles, such as 'Trumped' (Arntzenius and McCarthy 1997), 'Rouble trouble' (Arntzenius and Barrett 1999), 'The airtight Dutch book' (McGee 1999), and 'The two envelopes puzzle' (Broome 1995). Others are new. A unified resolution of the puzzles shows that Dutch book arguments have no force in infinite cases. It thereby provides evidence that reasonable utility functions may be unbounded and that reasonable credence functions need not be countably (...)
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  37. The Bayesians and the Raven Paradox.Jerrold L. Aronson - 1989 - Noûs 23 (2):221-240.
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  38. Practice-Oriented Controversies and Borrowed Epistemic Support in Current Evolutionary Biology: Phylogeography as a Case Study.Alfonso Arroyo-Santos, Mark E. Olson & Francisco Vergara-Silva - 2014 - Biology and Philosophy 29:833-850.
    Although there is increasing recognition that theory and practice in science are often inseparably intertwined, discussions of scientific controversies often continue to focus on theory, and not practice or methodologies. As a contribution to constructing a framework towards understanding controversies linked to scientific practices, we introduce the notion of borrowed epistemic credibility, to describe the situation in which scientists exploit fallacious similarities between accepted tenets in other fields to garner support for a given position in their own field. Our proposal (...)
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  39. Bayesian Statistics in Medicine: A 25 Year Review.Deborah Ashby - 2006 - Statistics in Medicine 25:3589-3631.
    This review examines the state of Bayesian thinking as Statistics in Medicine was launched in 1982, reflecting particularly on its applicability and uses in medical research. It then looks at each subsequent five-year epoch, with a focus on papers appearing in Statistics in Medicine , putting these in the context of major developments in Bayesian thinking and computation with reference to important books, landmark meetings and seminal papers. It charts the growth of Bayesian statistics as it is applied to medicine (...)
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  40. Reichenbach's Posits Reposited.David Atkinson & Jeanne Peijnenburg - 2008 - Erkenntnis 69 (1):93 - 108.
    Reichenbach’s use of ‘posits’ to defend his frequentistic theory of probability has been criticized on the grounds that it makes unfalsifiable predictions. The justice of this criticism has blinded many to Reichenbach’s second use of a posit, one that can fruitfully be applied to current debates within epistemology. We show first that Reichenbach’s alternative type of posit creates a difficulty for epistemic foundationalists, and then that its use is equivalent to a particular kind of Jeffrey conditionalization. We conclude that, under (...)
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  41. Psychological Probability as a Function of Experienced Frequency.Fred Attneave - 1953 - Journal of Experimental Psychology 46 (2):81.
  42. A Rational Analysis of Confirmation with Deterministic Hypotheses.J. Austerweil & T. Griffiths - 2008 - In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 1041--1046.
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  43. A Nonparametric Bayesian Framework for Constructing Flexible Feature Representations.Joseph L. Austerweil & Thomas L. Griffiths - 2013 - Psychological Review 120 (4):817-851.
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  44. Seeking Confirmation Is Rational for Deterministic Hypotheses.Joseph L. Austerweil & Thomas L. Griffiths - 2011 - Cognitive Science 35 (3):499-526.
    The tendency to test outcomes that are predicted by our current theory (the confirmation bias) is one of the best-known biases of human decision making. We prove that the confirmation bias is an optimal strategy for testing hypotheses when those hypotheses are deterministic, each making a single prediction about the next event in a sequence. Our proof applies for two normative standards commonly used for evaluating hypothesis testing: maximizing expected information gain and maximizing the probability of falsifying the current hypothesis. (...)
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  45. Are (the Log‐Odds of) Hospital Mortality Rates Normally Distributed? Implications for Studying Variations in Outcomes of Medical Care.Peter C. Austin - 2009 - Journal of Evaluation in Clinical Practice 15 (3):514-523.
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  46. Bayeswatch: An Overview of Bayesian Statistics.Peter C. Austin, Lawrence J. Brunner & Janet E. Hux M. D. Sm - 2002 - Journal of Evaluation in Clinical Practice 8 (2):277-286.
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  47. Bayeswatch: An Overview of Bayesian Statistics.Peter C. Austin, Lawrence J. Brunner & E. Janet - 2002 - Journal of Evaluation in Clinical Practice 8 (2):277-286.
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  48. A Comparison of a Bayesian Vs. A Frequentist Method for Profiling Hospital Performance.Peter C. Austin, C. David Naylor & Jack V. Tu - 2001 - Journal of Evaluation in Clinical Practice 7 (1):35-45.
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  49. Constraining Prior Probabilities of Phylogenetic Trees.Bengt Autzen - 2011 - Biology and Philosophy 26 (4):567-581.
    Although Bayesian methods are widely used in phylogenetic systematics today, the foundations of this methodology are still debated among both biologists and philosophers. The Bayesian approach to phylogenetic inference requires the assignment of prior probabilities to phylogenetic trees. As in other applications of Bayesian epistemology, the question of whether there is an objective way to assign these prior probabilities is a contested issue. This paper discusses the strategy of constraining the prior probabilities of phylogenetic trees by means of the Principal (...)
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  50. Probability and Evidence.A. J. Ayer - 1972 - [London]Macmillan.
    A. J. Ayer was one of the foremost analytical philosophers of the twentieth century, and was known as a brilliant and engaging speaker. In essays based on his influential Dewey Lectures, Ayer addresses some of the most critical and controversial questions in epistemology and the philosophy of science, examining the nature of inductive reasoning and grappling with the issues that most concerned him as a philosopher. This edition contains revised and expanded versions of the lectures and two additional essays. Ayer (...)
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