Results for 'Bayesian theory'

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  1.  91
    Bayes or Bust? A Critical Examination of Bayesian Confirmation Theory.John Earman - 1992 - MIT Press.
    There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes’s original paper to contemporary formal learning (...)
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  2. A Unified Bayesian Decision Theory.Richard Bradley - 2007 - Theory and Decision 63 (3):233-263,.
    This paper provides new foundations for Bayesian Decision Theory based on a representation theorem for preferences defined on a set of prospects containing both factual and conditional possibilities. This use of a rich set of prospects not only provides a framework within which the main theoretical claims of Savage, Ramsey, Jeffrey and others can be stated and compared, but also allows for the postulation of an extended Bayesian model of rational belief and desire from which they can (...)
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  3.  97
    Bayesian Decision Theory and Stochastic Independence.Philippe Mongin - 2020 - Philosophy of Science 87 (1):152-178.
    As stochastic independence is essential to the mathematical development of probability theory, it seems that any foundational work on probability should be able to account for this property. Bayesian decision theory appears to be wanting in this respect. Savage’s postulates on preferences under uncertainty entail a subjective expected utility representation, and this asserts only the existence and uniqueness of a subjective probability measure, regardless of its properties. What is missing is a preference condition corresponding to stochastic independence. (...)
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  4.  30
    Why is Bayesian Confirmation Theory Rarely Practiced?Robert W. P. Luk - 2019 - Science and Philosophy 7 (1):3-20.
    Bayesian confirmation theory is a leading theory to decide the confirmation/refutation of a hypothesis based on probability calculus. While it may be much discussed in philosophy of science, is it actually practiced in terms of hypothesis testing by scientists? Since the assignment of some of the probabilities in the theory is open to debate and the risk of making the wrong decision is unknown, many scientists do not use the theory in hypothesis testing. Instead, they (...)
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  5. Is There a Place in Bayesian Confirmation Theory for the Reverse Matthew Effect?William Roche - 2018 - Synthese 195 (4):1631-1648.
    Bayesian confirmation theory is rife with confirmation measures. Many of them differ from each other in important respects. It turns out, though, that all the standard confirmation measures in the literature run counter to the so-called “Reverse Matthew Effect” (“RME” for short). Suppose, to illustrate, that H1 and H2 are equally successful in predicting E in that p(E | H1)/p(E) = p(E | H2)/p(E) > 1. Suppose, further, that initially H1 is less probable than H2 in that p(H1) (...)
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  6. Bayesian Decision Theory and Stochastic Independence.Philippe Mongin - 2017 - TARK 2017.
    Stochastic independence has a complex status in probability theory. It is not part of the definition of a probability measure, but it is nonetheless an essential property for the mathematical development of this theory. Bayesian decision theorists such as Savage can be criticized for being silent about stochastic independence. From their current preference axioms, they can derive no more than the definitional properties of a probability measure. In a new framework of twofold uncertainty, we introduce preference axioms (...)
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  7.  22
    A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.Hongjing Lu, Randall R. Rojas, Tom Beckers & Alan L. Yuille - 2016 - Cognitive Science 40 (2):404-439.
    Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that (...)
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  8.  30
    Fine-Tuning in the Context of Bayesian Theory Testing.Luke A. Barnes - 2018 - European Journal for Philosophy of Science 8 (2):253-269.
    Fine-tuning in physics and cosmology is often used as evidence that a theory is incomplete. For example, the parameters of the standard model of particle physics are “unnaturally” small, which has driven much of the search for physics beyond the standard model. Of particular interest is the fine-tuning of the universe for life, which suggests that our universe’s ability to create physical life forms is improbable and in need of explanation, perhaps by a multiverse. This claim has been challenged (...)
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  9.  78
    Towards a Bayesian Theory of Second-Order Uncertainty: Lessons From Non- Standard Logics.Hykel Hosni - unknown
    Second-order uncertainty, also known as model uncertainty and Knightian uncertainty, arises when decision-makers can (partly) model the parameters of their decision problems. It is widely believed that subjective probability, and more generally Bayesian theory, are ill-suited to represent a number of interesting second-order uncertainty features, especially “ignorance” and “ambiguity”. This failure is sometimes taken as an argument for the rejection of the whole Bayesian approach, triggering a Bayes vs anti-Bayes debate which is in many ways analogous to (...)
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  10.  27
    Utility Theory and the Bayesian Paradigm.Jordan Howard Sobel - 1989 - Theory and Decision 26 (3):263-293.
  11. Betting on the Outcomes of Measurements: A Bayesian Theory of Quantum Probability.Itamar Pitowsky - 2002 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 34 (3):395-414.
    We develop a systematic approach to quantum probability as a theory of rational betting in quantum gambles. In these games of chance, the agent is betting in advance on the outcomes of several (finitely many) incompatible measurements. One of the measurements is subsequently chosen and performed and the money placed on the other measurements is returned to the agent. We show how the rules of rational betting imply all the interesting features of quantum probability, even in such finite gambles. (...)
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  12.  7
    Betting on the Outcomes of Measurements: A Bayesian Theory of Quantum Probability.Itamar Pitowsky - 2003 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 34 (3):395-414.
    We develop a systematic approach to quantum probability as a theory of rational betting in quantum gambles. In these games of chance the agent is betting in advance on the outcomes of several incompatible measurements. One of the measurements is subsequently chosen and performed and the money placed on the other measurements is returned to the agent. We show how the rules of rational betting imply all the interesting features of quantum probability, even in such finite gambles. These include (...)
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  13.  99
    Studies in Bayesian Confirmation Theory.Branden Fitelson - 2001 - Dissertation, University of Wisconsin, Madison
    According to Bayesian confirmation theory, evidence E (incrementally) confirms (or supports) a hypothesis H (roughly) just in case E and H are positively probabilistically correlated (under an appropriate probability function Pr). There are many logically equivalent ways of saying that E and H are correlated under Pr. Surprisingly, this leads to a plethora of non-equivalent quantitative measures of the degree to which E confirms H (under Pr). In fact, many non-equivalent Bayesian measures of the degree to which (...)
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  14.  34
    Acceptance of Empirical Statements: A Bayesian Theory Without Cognitive Utilities.John C. Harsanyi - 1985 - Theory and Decision 18 (1):1-30.
  15.  24
    Bayesian Theory Appraisal: A Reply to Seidenfeld.R. D. Rosenkrantz - 1979 - Theory and Decision 11 (4):441-451.
  16.  11
    How Pseudo-Hypotheses Defeat a Non-Bayesian Theory of Evidence: Reply to Bandyopadhyay, Taper, and Brittan.Colin Howson - 2016 - International Studies in the Philosophy of Science 30 (3):299-306.
    Bandyopadhyay, Taper, and Brittan advance a measure of evidential support that first appeared in the statistical and philosophical literature four decades ago and have been extensively discussed since. I have argued elsewhere, however, that it is vulnerable to a simple counterexample. BTB claim that the counterexample is flawed because it conflates evidence with confirmation. In this reply, I argue that the counterexample stands, and is fatal to their theory.
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  17.  45
    A Bayesian Theory of Rational Acceptance.Mark Kaplan - 1981 - Journal of Philosophy 78 (6):305-330.
  18. Explanatoriness is Evidentially Irrelevant, or Inference to the Best Explanation Meets Bayesian Confirmation Theory.W. Roche & E. Sober - 2013 - Analysis 73 (4):659-668.
    In the world of philosophy of science, the dominant theory of confirmation is Bayesian. In the wider philosophical world, the idea of inference to the best explanation exerts a considerable influence. Here we place the two worlds in collision, using Bayesian confirmation theory to argue that explanatoriness is evidentially irrelevant.
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  19.  65
    Some Recent Objections to the Bayesian Theory of Support.Colin Howson - 1985 - British Journal for the Philosophy of Science 36 (3):305-309.
  20. Bayesian Confirmation Theory: Inductive Logic, or Mere Inductive Framework?Michael Strevens - 2004 - Synthese 141 (3):365 - 379.
    Does the Bayesian theory of confirmation put real constraints on our inductive behavior? Or is it just a framework for systematizing whatever kind of inductive behavior we prefer? Colin Howson (Hume's Problem) has recently championed the second view. I argue that he is wrong, in that the Bayesian apparatus as it is usually deployed does constrain our judgments of inductive import, but also that he is right, in that the source of Bayesianism's inductive prescriptions is not the (...)
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  21. The Neyman-Pearson Theory as Decision Theory, and as Inference Theory; with a Criticism of the Lindley-Savage Argument for Bayesian Theory.Allan Birnbaum - 1977 - Synthese 36 (1):19 - 49.
  22.  32
    Accommodation, Prediction and Bayesian Confirmation Theory.Colin Howson - 1988 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1988:381 - 392.
    This paper examines the famous doctrine that independent prediction garners more support than accommodation. The standard arguments for the doctrine are found to be invalid, and a more realistic position is put forward, that whether evidence supports or not a hypothesis depends on the prior probability of the hypothesis, and is independent of whether it was proposed before or after the evidence. This position is implicit in the subjective Bayesian theory of confirmation, and the paper ends with a (...)
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  23.  27
    A Minimal Extension of Bayesian Decision Theory.Ken Binmore - 2016 - Theory and Decision 80 (3):341-362.
    Savage denied that Bayesian decision theory applies in large worlds. This paper proposes a minimal extension of Bayesian decision theory to a large-world context that evaluates an event E\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$E$$\end{document} by assigning it a number π\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi $$\end{document} that reduces to an orthodox probability for a class of measurable events. The Hurwicz criterion evaluates π\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} (...)
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  24. ``A Bayesian Theory of Acceptance&Quot.Mark Kaplan - 1981 - Journal of Philosophy 78 (6):305--30.
  25.  14
    Extending and Testing the Bayesian Theory of Generalization.Daniel J. Navarro, Michael D. Lee, Matthew J. Dry & Benjamin Schultz - 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.
  26.  57
    A Solution to a Problem for Bayesian Confirmation Theory.Richard Otte - 1994 - British Journal for the Philosophy of Science 45 (2):764-769.
    Charles Chihara has presented a problem he claims Bayesian confirmation theory cannot handle. Chihara gives examples in which he claims the change in belief cannot be construced as conditionalizing on new evidence. These are situations in which the agent suddenly thinks of new possibilities. I propose a solution that incorporates the important ideas of Bayesian theory. In particular, I present a principle which shows that the change of belief in Chihara's example is due to simple conditionalization.
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  27. Extending Bayesian Theory to Cooperative Groups: An Introduction to Indeterminate/Imprecise Probability Theories [IP] Also See Www.Sipta.Org.Teddy Seidenfeld & Mark Schervish - unknown
    Pi(AS) = Pi(A)Pi(S) for i = 1, 2. But the Linear Pool created a group opinion P3 with positive dependence. P3(A|S) > P3(A).
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  28.  8
    A Bayesian Theory of Thought.Howard Smokler - 1991 - Behavioral and Brain Sciences 14 (3):505-505.
  29. A Higher Order Bayesian Decision Theory of Consciousness.Hakwan Lau - 2008 - In Rahul Banerjee & B. K. Chakrabarti (eds.), Models of Brain and Mind: Physical, Computational, and Psychological Approaches. Elsevier.
    It is usually taken as given that consciousness involves superior or more elaborate forms of information processing. Contemporary models equate consciousness with global processing, system complexity, or depth or stability of computation. This is in stark contrast with the powerful philosophical intuition that being conscious is more than just having the ability to compute. I argue that it is also incompatible with current empirical findings. I present a model that is free from the strong assumption that consciousness predicts superior performance. (...)
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  30. Challenges to Bayesian Confirmation Theory.John D. Norton - 2011 - In Prasanta S. Bandyopadhyay & Malcolm R. Forster (eds.), Handbook of the Philosophy of Science, Vol. 7: Philosophy of Statistics. Elsevier B.V.. pp. 391-440.
    Proponents of Bayesian confirmation theory believe that they have the solution to a significant, recalcitrant problem in philosophy of science. It is the identification of the logic that governs evidence and its inductive bearing in science. That is the logic that lets us say that our catalog of planetary observations strongly confirms Copernicus’ heliocentric hypothesis; or that the fossil record is good evidence for the theory of evolution; or that the 3oK cosmic background radiation supports big bang (...)
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  31. Bayesian Confirmation Theory and The Likelihood Principle.Daniel Steel - 2007 - Synthese 156 (1):53-77.
    The likelihood principle (LP) is a core issue in disagreements between Bayesian and frequentist statistical theories. Yet statements of the LP are often ambiguous, while arguments for why a Bayesian must accept it rely upon unexamined implicit premises. I distinguish two propositions associated with the LP, which I label LP1 and LP2. I maintain that there is a compelling Bayesian argument for LP1, based upon strict conditionalization, standard Bayesian decision theory, and a proposition I call (...)
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  32.  85
    Notes on Bayesian Confirmation Theory.Michael Strevens - manuscript
    Bayesian confirmation theory—abbreviated to in these notes—is the predominant approach to confirmation in late twentieth century philosophy of science. It has many critics, but no rival theory can claim anything like the same following. The popularity of the Bayesian approach is due to its flexibility, its apparently effortless handling of various technical problems, the existence of various a priori arguments for its validity, and its injection of subjective and contextual elements into the process of confirmation in (...)
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  33. Bayesian Decision Theory, Subjective and Objective Probabilities, and Acceptance of Empirical Hypotheses.John C. Harsanyi - 1983 - Synthese 57 (3):341 - 365.
    It is argued that we need a richer version of Bayesian decision theory, admitting both subjective and objective probabilities and providing rational criteria for choice of our prior probabilities. We also need a theory of tentative acceptance of empirical hypotheses. There is a discussion of subjective and of objective probabilities and of the relationship between them, as well as a discussion of the criteria used in choosing our prior probabilities, such as the principles of indifference and of (...)
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  34.  45
    Bayesian Rationality for the Wason Selection Task? A Test of Optimal Data Selection Theory.Klaus Oberauer, Oliver Wilhelm & Ricardo Rosas Diaz - 1999 - Thinking and Reasoning 5 (2):115 – 144.
    Oaksford and Chater (1994) proposed to analyse the Wason selection task as an inductive instead of a deductive task. Applying Bayesian statistics, they concluded that the cards that participants tend to select are those with the highest expected information gain. Therefore, their choices seem rational from the perspective of optimal data selection. We tested a central prediction from the theory in three experiments: card selection frequencies should be sensitive to the subjective probability of occurrence for individual cards. In (...)
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  35.  33
    Heuristic Novelty and the Asymmetry Problem in Bayesian Confirmation Theory.Richard Nunan - 1993 - British Journal for the Philosophy of Science 44 (1):17-36.
    Bayesian confirmation theory, as traditionally interpreted, treats the temporal relationship between the formulation of a hypothesis and the confirmation (or recognition) of evidence entailed by that hypothesis merely as a component of the psychology of discovery and acceptance of a hypothesis. The temporal order of these events is irrelevant to the logic of rational theory choice. A few years ago Richmond Campbell and Thomas Vinci offered a reinterpretation of Bayes' Theorem in defense of the view that the (...)
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  36.  14
    Nested Sets Theory, Full Stop: Explaining Performance on Bayesian Inference Tasks Without Dual-Systems Assumptions.David R. Mandel - 2007 - Behavioral and Brain Sciences 30 (3):275-276.
    Consistent with Barbey & Sloman (B&S), it is proposed that performance on Bayesian inference tasks is well explained by nested sets theory (NST). However, contrary to those authors' view, it is proposed that NST does better by dispelling with dual-systems assumptions. This article examines why, and sketches out a series of NST's core principles, which were not previously defined.
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  37.  47
    Eliminative Induction and Bayesian Confirmation Theory.Susan Vineberg - 1996 - Canadian Journal of Philosophy 26 (2):257-66.
    In his recent book The Advancement of Science, Philip Kitcher endorses eliminative induction, or the view that confirmation of hypotheses proceeds by the elimination of alternatives. My intention here is to critically examine Kitcher's eliminativist view of confirmation, and his rejection of the widely held Bayesian position, according to which an hypothesis H is confirmed by evidence E just in case the probability of H conditional on E is greater than the simple unconditional probability of H [i.e. p > (...)
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  38.  17
    Non-Bayesian Confirmation Theory, and the Principle of Explanatory Surplus.Donald A. Gillies - 1988 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1988:373 - 380.
    This paper suggests a new principle for confirmation theory which is called the principle of explanatory surplus. This principle is shown to be non-Bayesian in character, and to lead to a treatment of simplicity in science. Two cases of the principle of explanatory surplus are considered. The first (number of parameters) is illustrated by curve-fitting examples, while the second (number of theoretical assumptions) is illustrated by the examples of Newton's Laws and Adler's Theory of the Inferiority Complex.
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  39. Probabilistic Confirmation Theory and Bayesian Reasoning.Timothy McGrew - manuscript
    This brief annotated bibliography is intended to help students get started with their research. It is not a substitute for personal investigation of the literature, and it is not a comprehensive bibliography on the subject. For those just beginning to study probabilistic confirmation theory and Bayesian reasoning, I suggest the starred items as good places to start your reading.
     
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  40.  5
    Eliminative Induction and Bayesian Confirmation Theory.Susan Vineberg - 1996 - Canadian Journal of Philosophy 26 (2):257-266.
    In his recent book The Advancement of Science, Philip Kitcher endorses eliminative induction, or the view that confirmation of hypotheses proceeds by the elimination of alternatives. My intention here is to critically examine Kitcher's eliminativist view of confirmation, and his rejection of the widely held Bayesian position, according to which an hypothesis H is confirmed by evidence E just in case the probability of H conditional on E is greater than the simple unconditional probability of H [i.e. p > (...)
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  41. Majority Rule, Rights, Utilitarianism, and Bayesian Group Decision Theory: Philosophical Essays in Decision-Theoretic Aggregation.Mathias Risse - 2000 - Dissertation, Princeton University
    My dissertation focuses on problems that arise when a group makes decisions that are in reasonable ways connected to the beliefs and values of the group members. These situations are represented by models of decision-theoretic aggregation: Suppose a model of individual rationality in decision-making applies to each of a group of agents. Suppose this model also applies to the group as a whole, and that this group model is aggregated from the individual models. Two questions arise. First, what sets of (...)
     
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  42.  79
    Bayesian Decision Theory in Sensorimotor Control.Konrad P. Körding & Daniel M. Wolpert - 2006 - Trends in Cognitive Sciences 10 (7):319-326.
  43.  75
    Theory-Based Bayesian Models of Inductive Learning and Reasoning.Joshua B. Tenenbaum, Thomas L. Griffiths & Charles Kemp - 2006 - Trends in Cognitive Sciences 10 (7):309-318.
  44. How Bayesian Confirmation Theory Handles the Paradox of the Ravens.Branden Fitelson & James Hawthorne - 2010 - In Ellery Eells & James Fetzer (eds.), The Place of Probability in Science. Springer. pp. 247--275.
    The Paradox of the Ravens (a.k.a,, The Paradox of Confirmation) is indeed an old chestnut. A great many things have been written and said about this paradox and its implications for the logic of evidential support. The first part of this paper will provide a brief survey of the early history of the paradox. This will include the original formulation of the paradox and the early responses of Hempel, Goodman, and Quine. The second part of the paper will describe attempts (...)
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  45.  59
    Bayesian Decision Theory, Rule Utilitarianism, and Arrow's Impossibility Theorem.John C. Harsanyi - 1979 - Theory and Decision 11 (3):289-317.
  46.  59
    A Theory of Bayesian Groups.Franz Dietrich - manuscript
    A group is often construed as a single agent with its own probabilistic beliefs (credences), which are obtained by aggregating those of the individuals, for instance through averaging. In their celebrated contribution “Groupthink”, Russell et al. (2015) apply the Bayesian paradigm to groups by requiring group credences to undergo a Bayesian revision whenever new information is learnt, i.e., whenever the individual credences undergo a Bayesian revision based on this information. Bayesians should often strengthen this requirement by extending (...)
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  47.  40
    Some Recent Fallacies of Approximation in Bayesian Confirmation Theory.Branden Fitelson - unknown
    • Several recent Bayesian discussions make use of “approximation” – Earman on the Quantitative Old Evidence Problem – Vranas on Quantitative Approaches to the Ravens Paradox – Dorling’s Quantitative Approach to Duhem–Quine – Strevens’s Quantitative Approach to Duhem–Quine – rThere are also examples not involving confirmation: E.g.
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  48.  16
    A Bayesian General Theory of Anthropic Reasoning.David Shulman - unknown
    A non-ad hoc, general theory of anthropic reasoning can be constructed based on Bostrom's Strong Self-Sampling Assumption that we should reason as if the current moment of our life were a randomly selected member of some appropriate reference class of observer-moments. We do not need to use anything other than standard conditionalization of a hypothetical prior based upon the SSSA in order to estimate probabilities. But we need to make the SSSA precise. We specify exactly what is and what (...)
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  49.  17
    Bayes or Bust?: A Critical Examination of Bayesian Confirmation Theory.Alan Hájek & Brian Skyrms - 2000 - Philosophy and Phenomenological Research 60 (3):707-711.
    A battered old philosophy of science vehicle heads west towards the Bayesian gold fields. Odd bits of junk are tied to the roof. In the rear window is a sign that reads “Bayes or Bust!” So far the story is not new. But at the wheel is a famous race car driver who has accelerated out of Newtonian space-time and decelerated back again.. Who could resist going along for the ride? We couldn’t—and you shouldn’t either.
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  50.  8
    Bayes or Bust?: A Critical Examination of Bayesian Confirmation Theory.Alan Hajek - 2000 - Philosophical and Phenomenological Research 60 (3):707-711.
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