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  1. S. B. (1997). Henri Poincare and Bruno de Finetti: Conventions and Scientific Reasoning. Studies in History and Philosophy of Science Part A 28 (4):657-679.
    In his account of probable reasoning, Poincare used the concept, or at least the language, of conventions. In particular, he claimed that the prior probabilities essential for inverse probable reasoning are determined conventionally. This paper investigates, in the light of Poincare's well known claim about the conventionality of metric geometry, what this could mean, and how it is related to other views about the determination of prior probabilities. Particular attention is paid to the similarities and differences between Poincare's conventionalism as (...)
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  2. José Luis Bermúdez (2011). Decision Theory and Rationality. OUP Oxford.
    The concept of rationality is a common thread through the human and social sciences -- from political science to philosophy, from economics to sociology, and from management science to decision analysis. But what counts as rational action and rational behavior? José Luis Bermúdez explores decision theory as a theory of rationality. Decision theory is the mathematical theory of choice and for many social scientists it makes the concept of rationality mathematically tractable and scientifically legitimate. Yet rationality is a concept with (...)
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  3. Lara Buchak (2012). Can It Be Rational to Have Faith? In Jacob Chandler & Victoria Harrison (eds.), Probability in the Philosophy of Religion. Oxford University Press. 225.
    This paper provides an account of what it is to have faith in a proposition p, in both religious and mundane contexts. It is argued that faith in p doesn’t require adopting a degree of belief that isn’t supported by one’s evidence but rather it requires terminating one’s search for further evidence and acting on the supposition that p. It is then shown, by responding to a formal result due to I.J. Good, that doing so can be rational in a (...)
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  4. Mandeep K. Dhami & David R. Mandel (2012). Forecasted Risk Taking in Youth: Evidence for a Bounded-Rationality Perspective. Synthese 189 (S1):161-171.
    This research examined whether youth's forecasted risk taking is best predicted by a compensatory (namely, subjective expected utility) or non-compensatory (e.g., single-factor) model. Ninety youth assessed the importance of perceived benefits, importance of perceived drawbacks, subjective probability of benefits, and subjective probability of drawbacks for 16 risky behaviors clustered evenly into recreational and health/safety domains. In both domains, there was strong support for a noncompensatory model in which only the perceived importance of the benefits of engaging in a risky behavior (...)
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  5. Georg J. W. Dorn (2005). Eine komparative Theorie der Stärke von Argumenten. Kriterion 19:34–43.
    This article presents a comparative theory of subjective argument strength simple enough for application. Using the axioms and corollaries of the theory, anyone with an elementary knowledge of logic and probability theory can produce an – at least minimally rational – ranking of any set of arguments according to their subjective strength, provided that the arguments in question are descriptive ones in standard form. The basic idea is that the strength of argument A as seen by person x is a (...)
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  6. Joseph S. Fulda (1988). Ratings and Confirmation. Quality and Quantity 22 (4):435-438.
    We present a linear formalism which makes explicit and precise the confirming effect of independent multiple observers and repeated trials on composite ratings, taking as parameters quantitative estimates of the subjective inputs discussed. -/- Note that the subjective probability used here is so used to study the past not predict the future and is rather limited to what has been called in artificial intelligence "certainty factors," which are arbitrary, or, more well-known, the arbitrary values ascribed to predicates in fuzzy "logic." (...)
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  7. Angelo Gilio & Giuseppe Sanfilippo (2013). Conjunction, Disjunction and Iterated Conditioning of Conditional Events. In R. Kruse (ed.), Advances in Intelligent Systems and Computing. Springer.
    Starting from a recent paper by S. Kaufmann, we introduce a notion of conjunction of two conditional events and then we analyze it in the setting of coherence. We give a representation of the conjoined conditional and we show that this new object is a conditional random quantity, whose set of possible values normally contains the probabilities assessed for the two conditional events. We examine some cases of logical dependencies, where the conjunction is a conditional event; moreover, we give the (...)
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  8. Jeremy Goodman (2013). Inexact Knowledge Without Improbable Knowing. Inquiry 56 (1):30-53.
    In a series of recent papers, Timothy Williamson has argued for the surprising conclusion that there are cases in which you know a proposition in spite of its being overwhelmingly improbable given what you know that you know it. His argument relies on certain formal models of our imprecise knowledge of the values of perceptible and measurable magnitudes. This paper suggests an alternative class of models that do not predict this sort of improbable knowing. I show that such models are (...)
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  9. Ian Hacking (1966). Review: Subjective Probability. [REVIEW] British Journal for the Philosophy of Science 16 (64):334 - 339.
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  10. Colin Howson (2012). Modelling Uncertain Inference. Synthese 186 (2):475-492.
    Kyburg’s opposition to the subjective Bayesian theory, and in particular to its advocates’ indiscriminate and often questionable use of Dutch Book arguments, is documented and much of it strongly endorsed. However, it is argued that an alternative version, proposed by both de Finetti at various times during his long career, and by Ramsey, is less vulnerable to Kyburg’s misgivings. This is a logical interpretation of the formalism, one which, it is argued, is both more natural and also avoids other, widely-made (...)
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  11. Cory Juhl (1993). Bayesianism and Reliable Scientific Inquiry. Philosophy of Science 60 (2):302-319.
    The inductive reliability of Bayesian methods is explored. The first result presented shows that for any solvable inductive problem of a general type, there exists a subjective prior which yields a Bayesian inductive method that solves the problem, although not all subjective priors give rise to a successful inductive method for the problem. The second result shows that the same does not hold for computationally bounded agents, so that Bayesianism is "inductively incomplete" for such agents. Finally a consistency proof shows (...)
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  12. Yusuke Kaneko (2012). BELIEF IN CAUSATION: ONE APPLICATION OF CARNAP's INDUCTIVE LOGIC. Academic Research International 3 (1).
    This paper takes two tasks. The one is elaborating on the relationship of inductive logic with decision theory to which later Carnap planned to apply his system (§§1-7); this is a surveying side of this article. The other is revealing the property of our prediction of the future, subjectivity (§§8-11); this is its philosophical aspect. They are both discussed under the name of belief in causation. Belief in causation is a kind of “degree of belief” born about the causal effect (...)
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  13. Yusuke Kaneko (2007). Belief as Probability. Philosophical Studies 25:107 - 20.
    In this paper, the philosophical concept of probability is investigated, referring to Ramsey's subjective theory and Carnap's inductive logic.
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  14. Henry E. Kyburg Jr (2001). Probability as a Guide in Life. The Monist 84 (2):135-152.
    Bishop Butler, [Butler, 1736], said that probability was the very guide of life. But what interpretations of probability can serve this function? It isn’t hard to see that empirical (frequency) views won’t do, and many recent writers-for example John Earman, who has said that Bayesianism is “the only game in town”-have been persuaded by various dutch book arguments that only subjective probability will perform the function required. We will defend the thesis that probability construed in this way offers very little (...)
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  15. Roger B. Myerson (1979). An Axiomatic Derivation of Subjective Probability, Utility, and Evaluation Functions. Theory and Decision 11 (4):339-352.
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  16. Wayne C. Myrvold (2012). Deterministic Laws and Epistemic Chances. In Yemima Ben-Menahem & Meir Hemmo (eds.), Probability in Physics. Springer. 73--85.
    In this paper, a concept of chance is introduced that is compatible with deterministic physical laws, yet does justice to our use of chance-talk in connection with typical games of chance. We take our cue from what Poincaré called "the method of arbitrary functions," and elaborate upon a suggestion made by Savage in connection with this. Comparison is made between this notion of chance, and David Lewis' conception.
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  17. Richard Pettigrew, Epistemic Utility Arguments for Probabilism. Stanford Encyclopedia.
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  18. Raghav Ramachandran, Arthur Ramer & Abhaya C. Nayak (2012). Probabilistic Belief Contraction. Minds and Machines 22 (4):325-351.
    Probabilistic belief contraction has been a much neglected topic in the field of probabilistic reasoning. This is due to the difficulty in establishing a reasonable reversal of the effect of Bayesian conditionalization on a probabilistic distribution. We show that indifferent contraction, a solution proposed by Ramer to this problem through a judicious use of the principle of maximum entropy, is a probabilistic version of a full meet contraction. We then propose variations of indifferent contraction, using both the Shannon entropy measure (...)
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  19. Susanna Rinard (2014). A New Bayesian Solution to the Paradox of the Ravens. Philosophy of Science 81 (1):81-100.
    The canonical Bayesian solution to the ravens paradox faces a problem: it entails that black non-ravens disconfirm the hypothesis that all ravens are black. I provide a new solution that avoids this problem. On my solution, black ravens confirm that all ravens are black, while non-black non-ravens and black non-ravens are neutral. My approach is grounded in certain relations of epistemic dependence, which, in turn, are grounded in the fact that the kind raven is more natural than the kind black. (...)
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  20. John Skilling (1985). Prior Probabilities. Synthese 63 (1):1 - 34.
    The theoretical construction and practical use of prior probabilities, in particular for systems having many degrees of freedom, are investigated. It becomes clear that it is operationally unsound to use mutually consistent priors if one wishes to draw sensible conclusions from practical experiments. The prior cannot usefully be identified with a state of knowledge, and indeed it is not so identified in common scientific practice. Rather, it can be identified with the question one asks. Accordingly, priors are free constructions. Their (...)
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  21. Weng Hong Tang (2012). Regularity Reformulated. Episteme 9 (4):329-343.
    This paper focuses on the view that rationality requires that our credences be regular. I go through different formulations of the requirement, and show that they face several problems. I then formulate a version of the requirement that solves most of, if not all, these problems. I conclude by showing that an argument thought to support the requirement as traditionally formulated actually does not; if anything, the argument, slightly modified, supports my version of the requirement.
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  22. Joel D. Velasco (2012). Objective and Subjective Probability in Gene Expression. Progress in Biophysics and Molecular Biology 110:5-10.
    In this paper I address the question of whether the probabilities that appear in models of stochastic gene expression are objective or subjective. I argue that while our best models of the phenomena in question are stochastic models, this fact should not lead us to automatically assume that the processes are inherently stochastic. After distinguishing between models and reality, I give a brief introduction to the philosophical problem of the interpretation of probability statements. I argue that the objective vs. subjective (...)
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  23. Byron E. Wall (2006). John Venn's Opposition to Probability as Degree of Belief. Studies in History and Philosophy of Science Part A 37 (4):550-561.
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  24. Elia Zardini (2012). Luminosity and Vagueness. Dialectica 66 (3):375-410.