Results for 'Probability'

999 found
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  1. Between Probability and Certainty: What Justifies Belief.Martin Smith - 2016 - Oxford University Press UK.
    This book explores a question central to philosophy--namely, what does it take for a belief to be justified or rational? According to a widespread view, whether one has justification for believing a proposition is determined by how probable that proposition is, given one's evidence. In this book this view is rejected and replaced with another: in order for one to have justification for believing a proposition, one's evidence must normically support it--roughly, one's evidence must make the falsity of that proposition (...)
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  2. Probability for Epistemic Modalities.Simon Goldstein & Paolo Santorio - 2021 - Philosophers' Imprint 21 (33).
    This paper develops an information-sensitive theory of the semantics and probability of conditionals and statements involving epistemic modals. The theory validates a number of principles linking probability and modality, including the principle that the probability of a conditional If A, then C equals the probability of C, updated with A. The theory avoids so-called triviality results, which are standardly taken to show that principles of this sort cannot be validated. To achieve this, we deny that rational (...)
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  3. Probability Without Tears.Julia Staffel - forthcoming - Teaching Philosophy.
    This paper is about teaching probability to students of philosophy who don’t aim to do primarily formal work in their research. These students are unlikely to seek out classes about probability or formal epistemology for various reasons, for example because they don’t realize that this knowledge would be useful for them or because they are intimidated by the material. However, most areas of philosophy now contain debates that incorporate probability, and basic knowledge of it is essential even (...)
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  4. Probabilities in Statistical Mechanics.Wayne C. Myrvold - 2016 - In Christopher Hitchcock & Alan H’Ajek (eds.), The Oxford Handbook of Probability and Philosophy. Oxford: Oxford University Press. pp. 573-600.
    This chapter will review selected aspects of the terrain of discussions about probabilities in statistical mechanics (with no pretensions to exhaustiveness, though the major issues will be touched upon), and will argue for a number of claims. None of the claims to be defended is entirely original, but all deserve emphasis. The first, and least controversial, is that probabilistic notions are needed to make sense of statistical mechanics. The reason for this is the same reason that convinced Maxwell, Gibbs, and (...)
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  5. Imprecise Probabilities and Unstable Betting Behaviour.Anna Mahtani - 2018 - Noûs 52 (1):69-87.
    Many have argued that a rational agent's attitude towards a proposition may be better represented by a probability range than by a single number. I show that in such cases an agent will have unstable betting behaviour, and so will behave in an unpredictable way. I use this point to argue against a range of responses to the ‘two bets’ argument for sharp probabilities.
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  6. Subjective Probability as Sampling Propensity.Thomas Icard - 2016 - Review of Philosophy and Psychology 7 (4):863-903.
    Subjective probability plays an increasingly important role in many fields concerned with human cognition and behavior. Yet there have been significant criticisms of the idea that probabilities could actually be represented in the mind. This paper presents and elaborates a view of subjective probability as a kind of sampling propensity associated with internally represented generative models. The resulting view answers to some of the most well known criticisms of subjective probability, and is also supported by empirical work (...)
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  7. Probabilities of Conditionals.Bas van Fraassen - 1976 - In C. Hooker (ed.), Foundations of probability theory, statistical inference, and statistical theories of science.
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  8. Subjective Probabilities Need Not Be Sharp.Jake Chandler - 2014 - Erkenntnis 79 (6):1273-1286.
    It is well known that classical, aka ‘sharp’, Bayesian decision theory, which models belief states as single probability functions, faces a number of serious difficulties with respect to its handling of agnosticism. These difficulties have led to the increasing popularity of so-called ‘imprecise’ models of decision-making, which represent belief states as sets of probability functions. In a recent paper, however, Adam Elga has argued in favour of a putative normative principle of sequential choice that he claims to be (...)
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  9.  82
    Probability and Arguments: Keynes’s Legacy.William Peden - 2021 - Cambridge Journal of Economics 45 (5):933–950.
    John Maynard Keynes’s A Treatise on Probability is the seminal text for the logical interpretation of probability. According to his analysis, probabilities are evidential relations between a hypothesis and some evidence, just like the relations of deductive logic. While some philosophers had suggested similar ideas prior to Keynes, it was not until his Treatise that the logical interpretation of probability was advocated in a clear, systematic and rigorous way. I trace Keynes’s influence in the philosophy of (...) through a heterogeneous sample of thinkers who adopted his interpretation. This sample consists of Frederick C. Benenson, Roy Harrod, Donald C. Williams, Henry E. Kyburg and David Stove. The ideas of Keynes prove to be adaptable to their diverse theories of probability. My discussion indicates both the robustness of Keynes’s probability theory and the importance of its influence on the philosophers whom I describe. I also discuss the Problem of the Priors. I argue that none of those I discuss have obviously improved on Keynes’s theory with respect to this issue. (shrink)
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  10. Evidential Probabilities and Credences.Anna-Maria Eder - 2019 - British Journal for the Philosophy of Science:1-21.
    Enjoying great popularity in decision theory, epistemology, and philosophy of science, Bayesianism as understood here is fundamentally concerned with epistemically ideal rationality. It assumes a tight connection between evidential probability and ideally rational credence, and usually interprets evidential probability in terms of such credence. Timothy Williamson challenges Bayesianism by arguing that evidential probabilities cannot be adequately interpreted as the credences of an ideal agent. From this and his assumption that evidential probabilities cannot be interpreted as the actual credences (...)
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  11. The Structure of Epistemic Probabilities.Nevin Climenhaga - 2020 - Philosophical Studies 177 (11):3213-3242.
    The epistemic probability of A given B is the degree to which B evidentially supports A, or makes A plausible. This paper is a first step in answering the question of what determines the values of epistemic probabilities. I break this question into two parts: the structural question and the substantive question. Just as an object’s weight is determined by its mass and gravitational acceleration, some probabilities are determined by other, more basic ones. The structural question asks what probabilities (...)
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  12. Conditional Probabilities.Kenny Easwaran - 2019 - In Richard Pettigrew & Jonathan Weisberg (eds.), The Open Handbook of Formal Epistemology. PhilPapers Foundation. pp. 131-198.
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  13. Indicative Conditionals: Probabilities and Relevance.Franz Berto & Aybüke Özgün - 2021 - Philosophical Studies.
    We propose a new account of indicative conditionals, giving acceptability and logical closure conditions for them. We start from Adams’ Thesis: the claim that the acceptability of a simple indicative equals the corresponding conditional probability. The Thesis is widely endorsed, but arguably false and refuted by empirical research. To fix it, we submit, we need a relevance constraint: we accept a simple conditional 'If φ, then ψ' to the extent that (i) the conditional probability p(ψ|φ) is high, provided (...)
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  14. Imprecise Probability and Higher Order Vagueness.Susanna Rinard - 2017 - Res Philosophica 94 (2):257-273.
    There is a trade-off between specificity and accuracy in existing models of belief. Descriptions of agents in the tripartite model, which recognizes only three doxastic attitudes—belief, disbelief, and suspension of judgment—are typically accurate, but not sufficiently specific. The orthodox Bayesian model, which requires real-valued credences, is perfectly specific, but often inaccurate: we often lack precise credences. I argue, first, that a popular attempt to fix the Bayesian model by using sets of functions is also inaccurate, since it requires us to (...)
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  15. Comparative Probabilities.Jason Konek - 2019 - In Richard Pettigrew & Jonathan Weisberg (eds.), The Open Handbook of Formal Epistemology. PhilPapers Foundation. pp. 267-348.
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  16. From Probabilities to Categorical Beliefs: Going Beyond Toy Models.Igor Douven & Hans Rott - 2018 - Journal of Logic and Computation 28 (6):1099-1124.
    According to the Lockean thesis, a proposition is believed just in case it is highly probable. While this thesis enjoys strong intuitive support, it is known to conflict with seemingly plausible logical constraints on our beliefs. One way out of this conflict is to make probability 1 a requirement for belief, but most have rejected this option for entailing what they see as an untenable skepticism. Recently, two new solutions to the conflict have been proposed that are alleged to (...)
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  17. On Probability and Cosmology: Inference Beyond Data?Martin Sahlen - 2017 - In K. Chamcham, J. Silk, J. D. Barrow & S. Saunders (eds.), The Philosophy of Cosmology. Cambridge, UK:
    Modern scientific cosmology pushes the boundaries of knowledge and the knowable. This is prompting questions on the nature of scientific knowledge. A central issue is what defines a 'good' model. When addressing global properties of the Universe or its initial state this becomes a particularly pressing issue. How to assess the probability of the Universe as a whole is empirically ambiguous, since we can examine only part of a single realisation of the system under investigation: at some point, data (...)
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  18. Imprecise Probabilities.Anna Mahtani - 2019 - In Richard Pettigrew & Jonathan Weisberg (eds.), The Open Handbook of Formal Epistemology. PhilPapers Foundation. pp. 107-130.
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  19. Probability in Ethics.David McCarthy - 2016 - In Alan Hájek & Christopher Hitchcock (eds.), The Oxford Handbook of Philosophy and Probability. Oxford University Press. pp. 705–737.
    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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  20. Infinitesimal Probabilities.Sylvia Wenmackers - 2016 - In Richard Pettigrew & Jonathan Weisberg (eds.), The Open Handbook of Formal Epistemology. PhilPapers Foundation. pp. 199-265.
    Non-Archimedean probability functions allow us to combine regularity with perfect additivity. We discuss the philosophical motivation for a particular choice of axioms for a non-Archimedean probability theory and answer some philosophical objections that have been raised against infinitesimal probabilities in general.
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  21. Probability and Randomness.Antony Eagle - 2016 - In Alan Hájek & Christopher Hitchcock (eds.), The Oxford Handbook of Probability and Philosophy. Oxford, U.K.: Oxford University Press. pp. 440-459.
    Early work on the frequency theory of probability made extensive use of the notion of randomness, conceived of as a property possessed by disorderly collections of outcomes. Growing out of this work, a rich mathematical literature on algorithmic randomness and Kolmogorov complexity developed through the twentieth century, but largely lost contact with the philosophical literature on physical probability. The present chapter begins with a clarification of the notions of randomness and probability, conceiving of the former as a (...)
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  22. 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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  23. Counterfactual Probability.Ginger Schultheis - forthcoming - Journal of Philosophy.
    Stalnaker's Thesis about indicative conditionals is, roughly, that the probability one ought to assign to an indicative conditional equals the probability that one ought to assign to its consequent conditional on its antecedent. The thesis seems right. If you draw a card from a standard 52-card deck, how confident are you that the card is a diamond if it's a red card? To answer this, you calculate the proportion of red cards that are diamonds -- that is, you (...)
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  24. Subjective Probabilities as Basis for Scientific Reasoning?Franz Huber - 2005 - British Journal for the Philosophy of Science 56 (1):101-116.
    Bayesianism is the position that scientific reasoning is probabilistic and that probabilities are adequately interpreted as an agent's actual subjective degrees of belief, measured by her betting behaviour. Confirmation is one important aspect of scientific reasoning. The thesis of this paper is the following: if scientific reasoning is at all probabilistic, the subjective interpretation has to be given up in order to get right confirmation—and thus scientific reasoning in general. The Bayesian approach to scientific reasoning Bayesian confirmation theory The example (...)
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  25. Symmetry Arguments Against Regular Probability: A Reply to Recent Objections.Matthew Parker - 2018 - European Journal for Philosophy of Science 9 (1):8.
    A probability distribution is regular if no possible event is assigned probability zero. While some hold that probabilities should always be regular, three counter-arguments have been posed based on examples where, if regularity holds, then perfectly similar events must have different probabilities. Howson (2017) and Benci et al. (2016) have raised technical objections to these symmetry arguments, but we see here that their objections fail. Howson says that Williamson’s (2007) “isomorphic” events are not in fact isomorphic, but Howson (...)
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  26. Bell’s Theorem, Quantum Probabilities, and Superdeterminism.Eddy Keming Chen - 2021 - In Eleanor Knox & Alastair Wilson (eds.), The Routledge Companion to Philosophy of Physics. Routledge.
    In this short survey article, I discuss Bell’s theorem and some strategies that attempt to avoid the conclusion of non-locality. I focus on two that intersect with the philosophy of probability: (1) quantum probabilities and (2) superdeterminism. The issues they raised not only apply to a wide class of no-go theorems about quantum mechanics but are also of general philosophical interest.
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  27. (Probably) Not Companions in Guilt.Sharon Berry - 2018 - Philosophical Studies 175 (9):2285-2308.
    In this paper, I will attempt to develop and defend a common form of intuitive resistance to the companions in guilt argument. I will argue that one can reasonably believe there are promising solutions to the access problem for mathematical realism that don’t translate to moral realism. In particular, I will suggest that the structuralist project of accounting for mathematical knowledge in terms of some form of logical knowledge offers significant hope of success while no analogous approach offers such hope (...)
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  28. Why Implicit Attitudes Are (Probably) Not Beliefs.Alex Madva - 2016 - Synthese 193 (8).
    Should we understand implicit attitudes on the model of belief? I argue that implicit attitudes are (probably) members of a different psychological kind altogether, because they seem to be insensitive to the logical form of an agent’s thoughts and perceptions. A state is sensitive to logical form only if it is sensitive to the logical constituents of the content of other states (e.g., operators like negation and conditional). I explain sensitivity to logical form and argue that it is a necessary (...)
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  29. A New Defence of Probability Discounting.Kian Mintz-Woo - 2017 - In Adrian Walsh, Säde Hormio & Duncan Purves (eds.), The Ethical Underpinnings of Climate Economics. Oxford: Routledge. pp. 87-102.
    When probability discounting (or probability weighting), one multiplies the value of an outcome by one's subjective probability that the outcome will obtain in decision-making. The broader import of defending probability discounting is to help justify cost-benefit analyses in contexts such as climate change. This chapter defends probability discounting under risk both negatively, from arguments by Simon Caney (2008, 2009), and with a new positive argument. First, in responding to Caney, I argue that small costs and (...)
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  30. Probability and Scepticism.Brian Weatherson - 2014 - In Dylan Dodd Elia Zardini (ed.), Scepticism and Perceptual Justification. Oxford University Press. pp. 71-86.
    If we add as an extra premise that the agent does know H, then it is possible for her to know E — H, we get the conclusion that the agent does not really know H. But even without that closure premise, or something like it, the conclusion seems quite dramatic. One possible response to the argument, floated by both Descartes and Hume, is to accept the conclusion and embrace scepticism. We cannot know anything that goes beyond our evidence, so (...)
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  31. Probability and Nonclassical Logic.Robert Williams - 2016 - In Alan Hajek & Christopher Hitchcock (eds.), The Oxford Handbook of Probability and Philosophy. Oxford university press.
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  32. 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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  33. 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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  34. Coherence, Probability and Explanation.William Roche & Michael Schippers - 2014 - Erkenntnis 79 (4):821-828.
    Recently there have been several attempts in formal epistemology to develop an adequate probabilistic measure of coherence. There is much to recommend probabilistic measures of coherence. They are quantitative and render formally precise a notion—coherence—notorious for its elusiveness. Further, some of them do very well, intuitively, on a variety of test cases. Siebel, however, argues that there can be no adequate probabilistic measure of coherence. Take some set of propositions A, some probabilistic measure of coherence, and a probability distribution (...)
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  35. Autonomous Killer Robots Are Probably Good News.Vincent C. Müller - 2016 - In Ezio Di Nucci & Filippo Santonio de Sio (eds.), Drones and responsibility: Legal, philosophical and socio-technical perspectives on the use of remotely controlled weapons. London: Ashgate. pp. 67-81.
    Will future lethal autonomous weapon systems (LAWS), or ‘killer robots’, be a threat to humanity? The European Parliament has called for a moratorium or ban of LAWS; the ‘Contracting Parties to the Geneva Convention at the United Nations’ are presently discussing such a ban, which is supported by the great majority of writers and campaigners on the issue. However, the main arguments in favour of a ban are unsound. LAWS do not support extrajudicial killings, they do not take responsibility away (...)
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  36.  60
    Probability and Certainty.Jonny Blamey - 2008 - Praxis 1 (1).
    Probability can be used to measure degree of belief in two ways: objectively and subjectively. The objective measure is a measure of the rational degree of belief in a proposition given a set of evidential propositions. The subjective measure is the measure of a particular subject’s dispositions to decide between options. In both measures, certainty is a degree of belief 1. I will show, however, that there can be cases where one belief is stronger than another yet both beliefs (...)
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  37. Probably the Charterhouse of Parma Does Not Exist, Possibly Not Even That Parma.Alberto Voltolini - 2013 - Humana Mente 6 (25):235-261.
    In this paper, I will claim that fictional works apparently about utterly immigrant objects, i.e., real individuals imported in fiction from reality, are instead about fictional individuals that intentionally resemble those real individuals in a significant manner: fictional surrogates of such individuals. Since I also share the realists’ conviction that the remaining fictional works concern native characters, i.e., full-fledged fictional individuals that originate in fiction itself, I will here defend a hyperrealist position according to which fictional works only concern fictional (...)
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  38. Probability Theory with Superposition Events.David Ellerman - manuscript
    In finite probability theory, events are subsets S⊆U of the outcome set. Subsets can be represented by 1-dimensional column vectors. By extending the representation of events to two dimensional matrices, we can introduce "superposition events." Probabilities are introduced for classical events, superposition events, and their mixtures by using density matrices. Then probabilities for experiments or `measurements' of all these events can be determined in a manner exactly like in quantum mechanics (QM) using density matrices. Moreover the transformation of the (...)
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  39. Dogmatism, Probability, and Logical Uncertainty.David Jehle & Brian Weatherson - 2012 - In Greg Restall & Gillian Kay Russell (eds.), New Waves in Philosophical Logic. Palgrave-Macmillan. pp. 95--111.
    Many epistemologists hold that an agent can come to justifiably believe that p is true by seeing that it appears that p is true, without having any antecedent reason to believe that visual impressions are generally reliable. Certain reliabilists think this, at least if the agent’s vision is generally reliable. And it is a central tenet of dogmatism (as described by Pryor (2000) and Pryor (2004)) that this is possible. Against these positions it has been argued (e.g. by Cohen (2005) (...)
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  40.  51
    Probability Modals and Infinite Domains.Adam Marushak - 2020 - Journal of Philosophical Logic 49 (5):1041-1055.
    Recent years have witnessed a proliferation of attempts to apply the mathematical theory of probability to the semantics of natural language probability talk. These sorts of “probabilistic” semantics are often motivated by their ability to explain intuitions about inferences involving “likely” and “probably”—intuitions that Angelika Kratzer’s canonical semantics fails to accommodate through a semantics based solely on an ordering of worlds and a qualitative ranking of propositions. However, recent work by Wesley Holliday and Thomas Icard has been widely (...)
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  41. Probability as a Guide to Life.Helen Beebee & David Papineau - 2003 - In David Papineau (ed.), The Roots of Reason. Oxford: Oxford University Press. pp. 217-243.
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  42. Fading Foundations: Probability and the Regress Problem.Jeanne Peijnenburg - 2017 - Cham, Switzerland: Springer.
    This Open Access book addresses the age-old problem of infinite regresses in epistemology. How can we ever come to know something if knowing requires having good reasons, and reasons can only be good if they are backed by good reasons in turn? The problem has puzzled philosophers ever since antiquity, giving rise to what is often called Agrippa's Trilemma. The current volume approaches the old problem in a provocative and thoroughly contemporary way. Taking seriously the idea that good reasons are (...)
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  43.  62
    Peirce, Pedigree, Probability.Rush T. Stewart & Tom F. Sterkenburg - forthcoming - Transactions of the Charles S. Peirce Society.
    An aspect of Peirce’s thought that may still be underappreciated is his resistance to what Levi calls _pedigree epistemology_, to the idea that a central focus in epistemology should be the justification of current beliefs. Somewhat more widely appreciated is his rejection of the subjective view of probability. We argue that Peirce’s criticisms of subjectivism, to the extent they grant such a conception of probability is viable at all, revert back to pedigree epistemology. A thoroughgoing rejection of pedigree (...)
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  44.  76
    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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  45.  60
    Probabilities on Sentences in an Expressive Logic.Marcus Hutter, John W. Lloyd, Kee Siong Ng & William T. B. Uther - 2013 - Journal of Applied Logic 11 (4):386-420.
    Automated reasoning about uncertain knowledge has many applications. One difficulty when developing such systems is the lack of a completely satisfactory integration of logic and probability. We address this problem directly. Expressive languages like higher-order logic are ideally suited for representing and reasoning about structured knowledge. Uncertain knowledge can be modeled by using graded probabilities rather than binary truth-values. The main technical problem studied in this paper is the following: Given a set of sentences, each having some probability (...)
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  46. Self-Referential Probability.Catrin Campbell-Moore - 2016 - Dissertation, Ludwig-Maximilians-Universität München
    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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  47.  36
    Probability of Guilt.Mario Günther - manuscript
    In legal proceedings, a fact-finder needs to decide whether a defendant is guilty or not based on probabilistic evidence. We defend the thesis that the defendant should be found guilty just in case it is rational for the fact-finder to believe that the defendant is guilty. We draw on Leitgeb’s stability theory for an appropriate notion of rational belief and show how our thesis solves the problem of statistical evidence. Finally, we defend our account of legal proof against challenges from (...)
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  48. The Perspectival Nature of Probability and Inference.Arnold Zuboff - 2000 - Inquiry: An Interdisciplinary Journal of Philosophy 43 (3):353 – 358.
    It is argued that two observers with the same information may rightly disagree about the probability of an event that they are both observing. This is a correct way of describing the view of a lottery outcome from the perspective of a winner and from the perspective of an observer not connected with the winner - the outcome is improbable for the winner and not improbable for the unconnected observer. This claim is both argued for and extended by developing (...)
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    Symmetry Arguments Against Regular Probability: A Reply to Recent Objections.Matthew Parker - 2019 - European Journal for Philosophy of Science 9 (1):1-21.
    A probability distribution is regular if it does not assign probability zero to any possible event. While some hold that probabilities should always be regular, three counter-arguments have been posed based on examples where, if regularity holds, then perfectly similar events must have different probabilities. Howson and Benci et al. have raised technical objections to these symmetry arguments, but we see here that their objections fail. Howson says that Williamson’s “isomorphic” events are not in fact isomorphic, but Howson (...)
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  50. Imprecise Probability and the Measurement of Keynes's "Weight of Arguments".William Peden - 2018 - IfCoLog Journal of Logics and Their Applications 5 (4):677-708.
    Many philosophers argue that Keynes’s concept of the “weight of arguments” is an important aspect of argument appraisal. The weight of an argument is the quantity of relevant evidence cited in the premises. However, this dimension of argumentation does not have a received method for formalisation. Kyburg has suggested a measure of weight that uses the degree of imprecision in his system of “Evidential Probability” to quantify weight. I develop and defend this approach to measuring weight. I illustrate the (...)
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