Results for 'Intersubjective Probability'

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  1.  27
    Intersubjective Probability and Confirmation Theory.Donald Gillies - 1991 - British Journal for the Philosophy of Science 42 (4):513-533.
    This paper introduces what is called the intersubjective interpretation of the probability calculus. Intersubjective probabilities are related to subjective probabilities, and the paper begins with a particular formulation of the familiar Dutch Book argument. This argument is then extended, in Section 3, to social groups, and this enables the concept of intersubjective probability to be introduced in Section 4. It is then argued that the intersubjective interpretation is the appropriate one for the probabilities which (...)
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  2. Group Level Interpretations of Probability: New Directions.Darrell P. Rowbottom - 2013 - Pacific Philosophical Quarterly 94 (2):188-203.
    In this article, I present some new group level interpretations of probability, and champion one in particular: a consensus-based variant where group degrees of belief are construed as agreed upon betting quotients rather than shared personal degrees of belief. One notable feature of the account is that it allows us to treat consensus between experts on some matter as being on the union of their relevant background information. In the course of the discussion, I also introduce a novel distinction (...)
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  3. Philosophical Theories of Probability.Donald Gillies - 2000 - Routledge.
    This book presents a comprehensive and systematic account of the various philosophical theories of probability and explains how they are related. It covers the classical, logical, subjective, frequency, and propensity views of probability. Donald Gillies even provides a new theory of probability -the intersubjective-a development of the subjective theory. He argues for a pluralist view, where there can be more than one valid interpretation of probabiltiy, each appropriate in a different context. The relation of the various (...)
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  4. Philosophical Theories of Probability.Donald Gillies - 2012 - Routledge.
    The Twentieth Century has seen a dramatic rise in the use of probability and statistics in almost all fields of research. This has stimulated many new philosophical ideas on probability. _Philosophical Theories of Probability_ is the first book to present a clear, comprehensive and systematic account of these various theories and to explain how they relate to one another. Gillies also offers a distinctive version of the propensity theory of probability, and the intersubjective interpretation, which develops (...)
     
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  5. Intersubjective Corroboration.Darrell P. Rowbottom - 2008 - Studies in History and Philosophy of Science Part A 39 (1):124-132.
    How are we to understand the use of probability in corroboration functions? Popper says logically, but does not show we could have access to, or even calculate, probability values in a logical sense. This makes the logical interpretation untenable, as Ramsey and van Fraassen have argued. -/- If corroboration functions only make sense when the probabilities employed therein are subjective, however, then what counts as impressive evidence for a theory might be a matter of convention, or even whim. (...)
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  6. Probability in Ethics.David McCarthy - forthcoming - In Alan Hájek & Christopher Hitchcock (eds.), The Oxford Handbook of Philosophy and Probability. Oxford University Press.
    The article is a plea for ethicists to regard probability as one of their most important concerns. It outlines a series of topics of central importance in ethical theory in which probability is implicated, often in a surprisingly deep way, and lists a number of open problems. Topics covered include: interpretations of probability in ethical contexts; the evaluative and normative significance of risk or uncertainty; uses and abuses of expected utility theory; veils of ignorance; Harsanyi’s aggregation theorem; (...)
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  7. The Conditional in Mental Probability Logic.Niki Pfeifer & G. D. Kleiter - 2010 - In M. Oaksford & N. Chater (eds.), Cognition and Conditionals: Probability and Logic in Human Thought. Oxford University Press. pp. 153--173.
    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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  8.  5
    The Semimeasure Property of Algorithmic Probability -- “Feature‘ or “Bug‘?Douglas Campbell - 2013 - In David L. Dowe (ed.), Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence: Papers From the Ray Solomonoff 85th Memorial Conference, Melbourne, Vic, Australia, November 30 -- December 2, 2011. Springer Berlin Heidelberg. pp. 79--90.
    An unknown process is generating a sequence of symbols, drawn from an alphabet, A. Given an initial segment of the sequence, how can one predict the next symbol? Ray Solomonoff’s theory of inductive reasoning rests on the idea that a useful estimate of a sequence’s true probability of being outputted by the unknown process is provided by its algorithmic probability (its probability of being outputted by a species of probabilistic Turing machine). However algorithmic probability is a (...)
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  9.  30
    Can Quantum Probability Provide a New Direction for Cognitive Modeling?Emmanuel M. Pothos & Jerome R. Busemeyer - 2013 - Behavioral and Brain Sciences 36 (3):255-274.
    Classical (Bayesian) probability (CP) theory has led to an influential research tradition for modeling cognitive processes. Cognitive scientists have been trained to work with CP principles for so long that it is hard even to imagine alternative ways to formalize probabilities. However, in physics, quantum probability (QP) theory has been the dominant probabilistic approach for nearly 100 years. Could QP theory provide us with any advantages in cognitive modeling as well? Note first that both CP and QP theory (...)
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  10. A Primer of Probability Logic.Ernest Adams - 1998 - Stanford: Csli Publications.
    This book is meant to be a primer, that is, an introduction, to probability logic, a subject that appears to be in its infancy. Probability logic is a subject envisioned by Hans Reichenbach and largely created by Adams. It treats conditionals as bearers of conditional probabilities and discusses an appropriate sense of validity for arguments such conditionals, as well as ordinary statements as premisses. This is a clear well-written text on the subject of probability logic, suitable for (...)
     
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  11. Deontic Modals and Probability: One Theory to Rule Them All?Fabrizio Cariani - forthcoming - In Nate Charlow & Matthew Chrisman (eds.), Deontic Modality. Oxford University Press.
    This paper motivates and develops a novel semantic framework for deontic modals. The framework is designed to shed light on two things: the relationship between deontic modals and substantive theories of practical rationality and the interaction of deontic modals with conditionals, epistemic modals and probability operators. I argue that, in order to model inferential connections between deontic modals and probability operators, we need more structure than is provided by classical intensional theories. In particular, we need probabilistic structure that (...)
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  12. Probability Operators.Seth Yalcin - 2010 - Philosophy Compass 5 (11):916-37.
    This is a study in the meaning of natural language probability operators, sentential operators such as probably and likely. We ask what sort of formal structure is required to model the logic and semantics of these operators. Along the way we investigate their deep connections to indicative conditionals and epistemic modals, probe their scalar structure, observe their sensitivity to contex- tually salient contrasts, and explore some of their scopal idiosyncrasies.
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  13. A Quantum Probability Account of Order Effects in Inference.Jennifer S. Trueblood & Jerome R. Busemeyer - 2011 - Cognitive Science 35 (8):1518-1552.
    Order of information plays a crucial role in the process of updating beliefs across time. In fact, the presence of order effects makes a classical or Bayesian approach to inference difficult. As a result, the existing models of inference, such as the belief-adjustment model, merely provide an ad hoc explanation for these effects. We postulate a quantum inference model for order effects based on the axiomatic principles of quantum probability theory. The quantum inference model explains order effects by transforming (...)
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  14. If-Clauses and Probability Operators.Paul Égré & Mikaël Cozic - 2011 - Topoi 30 (1):17-29.
    Adams’ thesis is generally agreed to be linguistically compelling for simple conditionals with factual antecedent and consequent. We propose a derivation of Adams’ thesis from the Lewis- Kratzer analysis of if-clauses as domain restrictors, applied to probability operators. We argue that Lewis’s triviality result may be seen as a result of inexpressibility of the kind familiar in generalized quantifier theory. Some implications of the Lewis- Kratzer analysis are presented concerning the assignment of probabilities to compounds of conditionals.
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  15.  46
    Mechanistic Probability.Marshall Abrams - 2012 - Synthese 187 (2):343-375.
    I describe a realist, ontologically objective interpretation of probability, "far-flung frequency (FFF) mechanistic probability". FFF mechanistic probability is defined in terms of facts about the causal structure of devices and certain sets of frequencies in the actual world. Though defined partly in terms of frequencies, FFF mechanistic probability avoids many drawbacks of well-known frequency theories and helps causally explain stable frequencies, which will usually be close to the values of mechanistic probabilities. I also argue that it's (...)
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  16. Objective Probability in Everettian Quantum Mechanics.A. Wilson - 2013 - British Journal for the Philosophy of Science 64 (4):709-737.
    David Wallace has given a decision-theoretic argument for the Born Rule in the context of Everettian quantum mechanics. This approach promises to resolve some long-standing problems with probability in EQM, but it has faced plenty of resistance. One kind of objection charges that the requisite notion of decision-theoretic uncertainty is unavailable in the Everettian picture, so that the argument cannot gain any traction; another kind of objection grants the proof’s applicability and targets the premises. In this article I propose (...)
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  17.  90
    Capturing the Relationship Between Conditionals and Conditional Probability with a Trivalent Semantics.Daniel Rothschild - 2014 - Journal of Applied Non-Classical Logics 24 (1-2):144-152.
    (2014). Capturing the relationship between conditionals and conditional probability with a trivalent semantics. Journal of Applied Non-Classical Logics: Vol. 24, Three-Valued Logics and their Applications, pp. 144-152. doi: 10.1080/11663081.2014.911535.
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  18.  26
    Conditional Probability in the Light of Qualitative Belief Change.David Makinson - 2011 - Journal of Philosophical Logic 40 (2):121 - 153.
    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, we explain how (...)
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  19.  9
    Confirmation, Increase in Probability, and the Likelihood Ratio Measure: A Reply to Glass and McCartney.Roche William - forthcoming - Acta Analytica.
    Bayesian confirmation theory is rife with confirmation measures. Zalabardo (2009) focuses on the probability difference measure, the probability ratio measure, the likelihood difference measure, and the likelihood ratio measure. He argues that the likelihood ratio measure is adequate but each of the other three measures is not. He argues for this by setting out three adequacy conditions on confirmation measures and arguing in effect that all of them are met by the likelihood ratio measure but not by any (...)
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  20. The Whole Truth About Linda: Probability, Verisimilitude and a Paradox of Conjunction.Gustavo Cevolani, Vincenzo Crupi & Roberto Festa - 2010 - In Marcello D'Agostino, Federico Laudisa, Giulio Giorello, Telmo Pievani & Corrado Sinigaglia (eds.), New Essays in Logic and Philosophy of Science. College Publications. pp. 603--615.
    We provide a 'verisimilitudinarian' analysis of the well-known Linda paradox or conjunction fallacy, i.e., the fact that most people judge the probability of the conjunctive statement "Linda is a bank teller and is active in the feminist movement" (B & F) as more probable than the isolated statement "Linda is a bank teller" (B), contrary to an uncontroversial principle of probability theory. The basic idea is that experimental participants may judge B & F a better hypothesis about Linda (...)
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  21. Deterministic Probability: Neither Chance nor Credence.Aidan Lyon - 2010 - Synthese 182 (3):413-432.
    Some have argued that chance and determinism are compatible in order to account for the objectivity of probabilities in theories that are compatible with determinism, like Classical Statistical Mechanics (CSM) and Evolutionary Theory (ET). Contrarily, some have argued that chance and determinism are incompatible, and so such probabilities are subjective. In this paper, I argue that both of these positions are unsatisfactory. I argue that the probabilities of theories like CSM and ET are not chances, but also that they are (...)
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  22.  29
    Explication of Inductive Probability.Patrick Maher - 2010 - Journal of Philosophical Logic 39 (6):593 - 616.
    Inductive probability is the logical concept of probability in ordinary language. It is vague but it can be explicated by defining a clear and precise concept that can serve some of the same purposes. This paper presents a general method for doing such an explication and then a particular explication due to Carnap. Common criticisms of Carnap's inductive logic are examined; it is shown that most of them are spurious and the others are not fundamental.
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  23. Naive Probability: A Mental Model Theory of Extensional Reasoning.Philip Johnson-Laird, Paolo Legrenzi, Vittorio Girotto, Maria Sonino Legrenzi & Jean-Paul Caverni - 1999 - Psychological Review 106 (1):62-88.
    This article outlines a theory of naive probability. According to the theory, individuals who are unfamiliar with the probability calculus can infer the probabilities of events in an extensional way: They construct mental models of what is true in the various possibilities. Each model represents an equiprobable alternative unless individuals have beliefs to the contrary, in which case some models will have higher probabilities than others. The probability of an event depends on the proportion of models in (...)
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  24. Non-Archimedean Probability.Vieri Benci, Leon Horsten & Sylvia Wenmackers - 2013 - Milan Journal of Mathematics 81 (1):121-151.
    We propose an alternative approach to probability theory closely related to the framework of numerosity theory: non-Archimedean probability (NAP). In our approach, unlike in classical probability theory, all subsets of an infinite sample space are measurable and only the empty set gets assigned probability zero (in other words: the probability functions are regular). We use a non-Archimedean field as the range of the probability function. As a result, the property of countable additivity in Kolmogorov’s (...)
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  25. Foundations of Probability.Rachael Briggs - forthcoming - Journal of Philosophical Logic:1-16.
    The foundations of probability are viewed through the lens of the subjectivist interpretation. This article surveys conditional probability, arguments for probabilism, probability dynamics, and the evidential and subjective interpretations of probability.
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  26.  39
    Self-Referential Probability.Catrin Campbell-Moore - unknown
    This thesis focuses on expressively rich languages that can formalise talk about probability. These languages have sentences that say something about probabilities of probabilities, but also sentences that say something about the probability of themselves. For example: (π): “The probability of the sentence labelled π is not greater than 1/2.” Such sentences lead to philosophical and technical challenges; but can be useful. For example they bear a close connection to situations where ones confidence in something can affect (...)
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  27.  94
    Updating: A Psychologically Basic Situation of Probability Revision.Jean Baratgin & Guy Politzer - 2011 - Thinking and Reasoning 16 (4):253-287.
    The Bayesian model has been used in psychology as the standard reference for the study of probability revision. In the first part of this paper we show that this traditional choice restricts the scope of the experimental investigation of revision to a stable universe. This is the case of a situation that, technically, is known as focusing. We argue that it is essential for a better understanding of human probability revision to consider another situation called updating (Katsuno & (...)
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  28.  36
    The Propensity Interpretation of Fitness and the Propensity Interpretation of Probability.Isabelle Drouet & Francesca Merlin - 2015 - Erkenntnis 80 (3):457-468.
    The paper provides a new critical perspective on the propensity interpretation of fitness, by investigating its relationship to the propensity interpretation of probability. Two main conclusions are drawn. First, the claim that fitness is a propensity cannot be understood properly: fitness is not a propensity in the sense prescribed by the propensity interpretation of probability. Second, this interpretation of probability is inessential for explanations proposed by the PIF in evolutionary biology. Consequently, interpreting the probabilistic dimension of fitness (...)
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  29. Conditional Probability From an Ontological Point of View.Rani Lill Anjum, Johan Arnt Myrstad & Stephen Mumford - manuscript
    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 conditional statements. (...)
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  30.  6
    A Condition for Transitivity in High Probability.William Roche - forthcoming - European Journal for Philosophy of Science:1-10.
    There are many scientific and everyday cases where each of Pr and Pr is high and it seems that Pr is high. But high probability is not transitive and so it might be in such cases that each of Pr and Pr is high and in fact Pr is not high. There is no issue in the special case where the following condition, which I call “C1”, holds: H1 entails H2. This condition is sufficient for transitivity in high (...). But many of the scientific and everyday cases referred to above are cases where it is not the case that H1 entails H2. I consider whether there are additional conditions sufficient for transitivity in high probability. I consider three candidate conditions. I call them “C2”, “C3”, and “C2&3”. I argue that C2&3, but neither C2 nor C3, is sufficient for transitivity in high probability. I then set out some further results and relate the discussion to the Bayesian requirement of coherence. (shrink)
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  31.  56
    Sets of Probability Distributions, Independence, and Convexity.Fabio G. Cozman - 2012 - Synthese 186 (2):577-600.
    This paper analyzes concepts of independence and assumptions of convexity in the theory of sets of probability distributions. The starting point is Kyburg and Pittarelli’s discussion of “convex Bayesianism” (in particular their proposals concerning E-admissibility, independence, and convexity). The paper offers an organized review of the literature on independence for sets of probability distributions; new results on graphoid properties and on the justification of “strong independence” (using exchangeability) are presented. Finally, the connection between Kyburg and Pittarelli’s results and (...)
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  32.  14
    Transitivity in Coherence-Based Probability Logic.Angelo Gilio, Niki Pfeifer & Giuseppe Sanfilippo - 2016 - Journal of Applied Logic 14:46-64.
    We study probabilistically informative (weak) versions of transitivity by using suitable definitions of defaults and negated defaults in the setting of coherence and imprecise probabilities. We represent p-consistent sequences of defaults and/or negated defaults by g-coherent imprecise probability assessments on the respective sequences of conditional events. Moreover, we prove the coherent probability propagation rules for Weak Transitivity and the validity of selected inference patterns by proving p-entailment of the associated knowledge bases. Finally, we apply our results to study (...)
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  33.  4
    Johannes von Kries’s Objective Probability as a Semi-Classical Concept. Prehistory, Preconditions and Problems of a Progressive Idea.Helmut Pulte - 2016 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 47 (1):109-129.
    Johannes von Kries’s Spielraum-theory is regarded as one of the most important philosophical contributions of the nineteenth century to an objective interpretation of probability. This paper aims at a critical and contextual analysis of von Kries’s approach: It is contextual insofar as it reconstructs the Spielraum-theory in the historical setting that formed his scientific and philosophical outlook. It is critical insofar as it unfolds systematic tensions and inconsistencies which are rooted in this context, especially in the grave change of (...)
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  34.  66
    Non-Monotonic Probability Theory and Photon Polarization.Fred Kronz - 2007 - Journal of Philosophical Logic 36 (4):449-472.
    A non-monotonic theory of probability is put forward and shown to have applicability in the quantum domain. It is obtained simply by replacing Kolmogorov's positivity axiom, which places the lower bound for probabilities at zero, with an axiom that reduces that lower bound to minus one. Kolmogorov's theory of probability is monotonic, meaning that the probability of A is less then or equal to that of B whenever A entails B. The new theory violates monotonicity, as its (...)
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  35. Popper’s Laws of the Excess of the Probability of the Conditional Over the Conditional Probability.Georg J. W. Dorn - 1992/93 - Conceptus: Zeitschrift Fur Philosophie 26:3–61.
    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 the material conditional (...)
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  36.  6
    Confirmation, Increase in Probability, and Partial Discrimination: A Reply to Zalabardo.William Roche - 2016 - European Journal for Philosophy of Science 6 (1):1-7.
    There is a plethora of confirmation measures in the literature. Zalabardo considers four such measures: PD, PR, LD, and LR. He argues for LR and against each of PD, PR, and LD. First, he argues that PR is the better of the two probability measures. Next, he argues that LR is the better of the two likelihood measures. Finally, he argues that LR is superior to PR. I set aside LD and focus on the trio of PD, PR, and (...)
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  37.  98
    Probably Good Diagrams for Learning: Representational Epistemic Recodification of Probability Theory.Peter C.-H. Cheng - 2011 - Topics in Cognitive Science 3 (3):475-498.
    The representational epistemic approach to the design of visual displays and notation systems advocates encoding the fundamental conceptual structure of a knowledge domain directly in the structure of a representational system. It is claimed that representations so designed will benefit from greater semantic transparency, which enhances comprehension and ease of learning, and plastic generativity, which makes the meaningful manipulation of the representation easier and less error prone. Epistemic principles for encoding fundamental conceptual structures directly in representational schemes are described. The (...)
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  38.  44
    Iterative Probability Kinematics.Horacio Arló-Costa & Richmond H. Thomason - 2001 - Journal of Philosophical Logic 30 (5):479-524.
    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 as (...)
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  39.  57
    Probability.Antony Eagle - 2015 - The Oxford Handbook of Philosophy of Science.
    Rather than entailing that a particular outcome will occur, many scientific theories only entail that an outcome will occur with a certain probability. Because scientific evidence inevitably falls short of conclusive proof, when choosing between different theories it is standard to make reference to how probable the various options are in light of the evidence. A full understanding of probability in science needs to address both the role of probabilities in theories, or chances, as well as the role (...)
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  40. Philosophy of Probability: Contemporary Readings.Antony Eagle (ed.) - 2010 - Routledge.
    Philosophy of Probability: Contemporary Readings is the first anthology to collect essential readings in this important area of philosophy. Featuring the work of leading philosophers in the field such as Carnap, Hájek, Jeffrey, Joyce, Lewis, Loewer, Popper, Ramsey, van Fraassen, von Mises, and many others, the book looks in depth at the following key topics: subjective probability and credence probability updating: conditionalization and reflection Bayesian confirmation theory classical, logical, and evidential probability frequentism physical probability: propensities (...)
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  41.  34
    Cardinality Arguments Against Regular Probability Measures.Thomas Hofweber - 2014 - Thought: A Journal of Philosophy 3 (2):166-175.
    Cardinality arguments against regular probability measures aim to show that no matter which ordered field ℍ we select as the measures for probability, we can find some event space F of sufficiently large cardinality such that there can be no regular probability measure from F into ℍ. In particular, taking ℍ to be hyperreal numbers won't help to guarantee that probability measures can always be regular. I argue that such cardinality arguments fail, since they rely on (...)
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  42.  42
    Causation, Probability, and the Continuity Bind.Anthony F. Peressini - forthcoming - British Journal for the Philosophy of Science:axw030.
    Analyses of singular (token-level) causation often make use of the idea that a cause in- creases the probability of its effect. Of particular salience in such accounts are the values of the probability function of the effect, conditional on the presence and absence of the putative cause, analyzed around the times of the events in question: causes are characterized by the effect’s probability function being greater when conditionalized upon them. Put this way it becomes clearer that the (...)
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  43. Natural-Born Deterministe: A New Defense of Causation as Probability-Raising.Robert Northcott - 2010 - Philosophical Studies 150 (1):1 - 20.
    A definition of causation as probability-raising is threatened by two kinds of counterexample: first, when a cause lowers the probability of its effect; and second, when the probability of an effect is raised by a non-cause. In this paper, I present an account that deals successfully with problem cases of both these kinds. In doing so, I also explore some novel implications of incorporating into the metaphysical investigation considerations of causal psychology.
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  44.  47
    From Classical to Intuitionistic Probability.Brian Weatherson - 2003 - Notre Dame Journal of Formal Logic 44 (2):111-123.
    We generalize the Kolmogorov axioms for probability calculus to obtain conditions defining, for any given logic, a class of probability functions relative to that logic, coinciding with the standard probability functions in the special case of classical logic but allowing consideration of other classes of "essentially Kolmogorovian" probability functions relative to other logics. We take a broad view of the Bayesian approach as dictating inter alia that from the perspective of a given logic, rational degrees of (...)
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  45.  28
    Hans Reichenbach.The Concept of Probability in the Mathematical Representation of Reality. Trans. And Ed. Frederick Eberhardt and Clark Glymour. Chicago: Open Court, 2008. Pp. Xi+154. $34.97. [REVIEW]Flavia Padovani - 2011 - Hopos: The Journal of the International Society for the History of Philosophy of Science 1 (2):344-347.
    Hans Reichenbach has been not only one of the founding fathers of logical empiricism but also one of the most prominent figures in the philosophy of science of the past century. While some of his ideas continue to be of interest in current philosophical programs, an important part of his early work has been neglected, and some of it has been unavailable to English readers. Among Reichenbach’s overlooked (and untranslated) early works, his doctoral thesis of 1915, The Concept of (...) in the Mathematical Representation of Reality, deserves special attention, both for the topics covered and for its significance for a proper understanding of his intellectual trajectory. This volume anticipates most of the fundamental themes of his later philosophy. In particular, it addresses the issue of the application of probability statements to reality, as well as the relationship between probability and causality—questions that have been at the core of his research throughout his life. (shrink)
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  46. Pollock on Probability in Epistemology. [REVIEW]Branden Fitelson - 2010 - Philosophical Studies 148 (3):455 - 465.
    In Thinking and Acting John Pollock offers some criticisms of Bayesian epistemology, and he defends an alternative understanding of the role of probability in epistemology. Here, I defend the Bayesian against some of Pollock's criticisms, and I discuss a potential problem for Pollock's alternative account.
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  47.  47
    Normativity, Probability, and Meta-Vagueness.Masaki Ichinose - forthcoming - Synthese:1-22.
    This paper engages with a specific problem concerning the relationship between descriptive and normative claims. Namely, if we understand that descriptive claims frequently contain normative assertions, and vice versa, how then do we interpret the traditionally rigid distinction that is made between the two, as ’Hume’s law’ or Moore’s ’naturalistic fallacy’ argument offered. In particular, Kripke’s interpretation of Wittgenstein’s ’rule-following paradox’ is specially focused upon in order to re-consider the rigid distinction. As such, the paper argues that if descriptive and (...)
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    Regular Probability Comparisons Imply the Banach–Tarski Paradox.Alexander R. Pruss - 2014 - Synthese 191 (15):3525-3540.
    Consider the regularity thesis that each possible event has non-zero probability. Hájek challenges this in two ways: there can be nonmeasurable events that have no probability at all and on a large enough sample space, some probabilities will have to be zero. But arguments for the existence of nonmeasurable events depend on the axiom of choice. We shall show that the existence of anything like regular probabilities is by itself enough to imply a weak version of AC sufficient (...)
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    Is There a Dutch Book Argument for Probability Kinematics?Brad Armendt - 1980 - Philosophy of Science 47 (4):583-588.
    Dutch Book arguments have been presented for static belief systems and for belief change by conditionalization. An argument is given here that a rule for belief change which under certain conditions violates probability kinematics will leave the agent open to a Dutch Book.
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    Probability Propagation in Generalized Inference Forms.Christian Wallmann & Gernot D. Kleiter - 2014 - Studia Logica 102 (4):913-929.
    Probabilistic inference forms lead from point probabilities of the premises to interval probabilities of the conclusion. The probabilistic version of Modus Ponens, for example, licenses the inference from \({P(A) = \alpha}\) and \({P(B|A) = \beta}\) to \({P(B)\in [\alpha\beta, \alpha\beta + 1 - \alpha]}\) . We study generalized inference forms with three or more premises. The generalized Modus Ponens, for example, leads from \({P(A_{1}) = \alpha_{1}, \ldots, P(A_{n})= \alpha_{n}}\) and \({P(B|A_{1} \wedge \cdots \wedge A_{n}) = \beta}\) to an according interval for (...)
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