Results for 'Credence, degree of belief, Bayesian, perception'

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  1. Conditional Degree of Belief and Bayesian Inference.Jan Sprenger - 2020 - Philosophy of Science 87 (2):319-335.
    Why are conditional degrees of belief in an observation E, given a statistical hypothesis H, aligned with the objective probabilities expressed by H? After showing that standard replies are not satisfactory, I develop a suppositional analysis of conditional degree of belief, transferring Ramsey’s classical proposal to statistical inference. The analysis saves the alignment, explains the role of chance-credence coordination, and rebuts the charge of arbitrary assessment of evidence in Bayesian inference. Finally, I explore the implications of this analysis for (...)
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  2. Perception and probability.Alex Byrne - 2021 - Philosophy and Phenomenological Research 104 (2):1-21.
    One very popular framework in contemporary epistemology is Bayesian. The central epistemic state is subjective confidence, or credence. Traditional epistemic states like belief and knowledge tend to be sidelined, or even dispensed with entirely. Credences are often introduced as familiar mental states, merely in need of a special label for the purposes of epistemology. But whether they are implicitly recognized by the folk or posits of a sophisticated scientific psychology, they do not appear to fit well with perception, as (...)
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  3. Reliability for degrees of belief.Jeff Dunn - 2015 - Philosophical Studies 172 (7):1929-1952.
    We often evaluate belief-forming processes, agents, or entire belief states for reliability. This is normally done with the assumption that beliefs are all-or-nothing. How does such evaluation go when we’re considering beliefs that come in degrees? I consider a natural answer to this question that focuses on the degree of truth-possession had by a set of beliefs. I argue that this natural proposal is inadequate, but for an interesting reason. When we are dealing with all-or-nothing belief, high reliability leads (...)
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  4. Perceptual experience and degrees of belief.Thomas Raleigh & Filippo Vindrola - 2020 - Philosophical Quarterly (2):378-406.
    According to the recent Perceptual Confidence view, perceptual experiences possess not only a representational content, but also a degree of confidence in that content. The motivations for this view are partly phenomenological and partly epistemic. We discuss both the phenomenological and epistemic motivations for the view, and the resulting account of the interface between perceptual experiences and degrees of belief. We conclude that, in their present state of development, orthodox accounts of perceptual experience are still to be favoured over (...)
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  5. Degree-of-belief and degree-of-support: Why bayesians need both notions.James Hawthorne - 2005 - Mind 114 (454):277-320.
    I argue that Bayesians need two distinct notions of probability. We need the usual degree-of-belief notion that is central to the Bayesian account of rational decision. But Bayesians also need a separate notion of probability that represents the degree to which evidence supports hypotheses. Although degree-of-belief is well suited to the theory of rational decision, Bayesians have tried to apply it to the realm of hypothesis confirmation as well. This double duty leads to the problem of old (...)
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  6. Belief Is Credence One (in Context).Roger Clarke - 2013 - Philosophers' Imprint 13:1-18.
    This paper argues for two theses: that degrees of belief are context sensitive; that outright belief is belief to degree 1. The latter thesis is rejected quickly in most discussions of the relationship between credence and belief, but the former thesis undermines the usual reasons for doing so. Furthermore, identifying belief with credence 1 allows nice solutions to a number of problems for the most widely-held view of the relationship between credence and belief, the threshold view. I provide a (...)
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  7. Vagueness, Uncertainty and Degrees of Belief: Two Kinds of Indeterminacy—One Kind of Credence.Nicholas J. J. Smith - 2014 - Erkenntnis 79 (5):1027-44.
    If we think, as Ramsey did, that a degree of belief that P is a stronger or weaker tendency to act as if P, then it is clear that not only uncertainty, but also vagueness, gives rise to degrees of belief. If I like hot coffee and do not know whether the coffee is hot or cold, I will have some tendency to reach for a cup; if I like hot coffee and know that the coffee is borderline hot, (...)
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  8.  81
    Fundamentals of Bayesian Epistemology 1: Introducing Credences.Michael G. Titelbaum - 2022 - Oxford University Press.
    'Fundamentals of Bayesian Epistemology' provides an accessible introduction to the key concepts and principles of the Bayesian formalism. This volume introduces degrees of belief as a concept in epistemology and the rules for updating degrees of belief derived from Bayesian principles.--.
  9. Quitting certainties: a Bayesian framework modeling degrees of belief.Michael G. Titelbaum - 2013 - Oxford: Oxford University Press.
    Michael G. Titelbaum presents a new Bayesian framework for modeling rational degrees of belief—the first of its kind to represent rational requirements on agents who undergo certainty loss.
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  10. The relation between degrees of belief and binary beliefs: A general impossibility theorem.Franz Dietrich & Christian List - 2021 - In Igor Douven (ed.), Lotteries, Knowledge, and Rational Belief. Essays on the Lottery Paradox. Cambridge University Press. pp. 223-54.
    Agents are often assumed to have degrees of belief (“credences”) and also binary beliefs (“beliefs simpliciter”). How are these related to each other? A much-discussed answer asserts that it is rational to believe a proposition if and only if one has a high enough degree of belief in it. But this answer runs into the “lottery paradox”: the set of believed propositions may violate the key rationality conditions of consistency and deductive closure. In earlier work, we showed that this (...)
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  11. Frá skoðunum til trúnaðar og aftur til baka: Yfirlit um bayesíska þekkingarfræði [English title: "From Belief to Credence and Back Again: An Overview of Bayesian Epistemology"].Finnur Dellsén - 2017 - Hugur 28:146-162.
    English abstract: This paper discusses the delicate relationship between traditional epistemology and the increasingly influential probabilistic (or ‘Bayesian’) approach to epistemology. The paper introduces some of the key ideas of probabilistic epistemology, including credences or degrees of belief, Bayes’ theorem, conditionalization, and the Dutch Book argument. The tension between traditional and probabilistic epistemology is brought out by considering the lottery and preface paradoxes as they relate to rational (binary) belief and credence respectively. It is then argued that this tension can (...)
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  12. Rational Agnosticism and Degrees of Belief.Jane Friedman - 2013 - Oxford Studies in Epistemology 4:57.
    There has been much discussion about whether traditional epistemology's doxastic attitudes are reducible to degrees of belief. In this paper I argue that what I call the Straightforward Reduction - the reduction of all three of believing p, disbelieving p, and suspending judgment about p, not-p to precise degrees of belief for p and not-p that ought to obey the standard axioms of the probability calculus - cannot succeed. By focusing on suspension of judgment (agnosticism) rather than belief, we can (...)
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  13.  78
    Degrees of belief, expected and actual.Rosanna Keefe - 2017 - Synthese 194 (10):3789-3800.
    A framework of degrees of belief, or credences, is often advocated to model our uncertainty about how things are or will turn out. It has also been employed in relation to the kind of uncertainty or indefiniteness that arises due to vagueness, such as when we consider “a is F” in a case where a is borderline F. How should we understand degrees of belief when we take into account both these phenomena? Can the right kind of theory of the (...)
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  14.  5
    Degree of Influence on Perception of Belief and Social Setting: Its Relevance to Understanding Pendulum Motion.Dennis Lomas - 2004 - Science & Education 13 (7-8):733-742.
  15. Knowing our degrees of belief.Sinan Dogramaci - 2016 - Episteme 13 (3):269-287.
    The main question of this paper is: how do we manage to know what our own degrees of belief are? Section 1 briefly reviews and criticizes the traditional functionalist view, a view notably associated with David Lewis and sometimes called the theory-theory. I use this criticism to motivate the approach I want to promote. Section 2, the bulk of the paper, examines and begins to develop the view that we have a special kind of introspective access to our degrees of (...)
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  16.  20
    Nonstandard Bayesianism: How Verisimilitude and Counterfactual Degrees of Belief Solve the Interpretive Problem in Bayesian Inference.Olav B. Vassend - unknown
    Scientists and Bayesian statisticians often study hypotheses that they know to be false. This creates an interpretive problem because the Bayesian probability of a hypothesis is typically interpreted as a degree of belief that the hypothesis is true. In this paper, I present and contrast two solutions to the interpretive problem, both of which involve reinterpreting the Bayesian framework in such a way that pragmatic factors directly determine in part how probability assignments are interpreted and whether a given probability (...)
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  17. 'In Between Believing' and Degrees of Belief.Darrell P. Rowbottom - 2007 - Teorema: International Journal of Philosophy 26 (1):131-137.
    Schwitzgebel (2001) — henceforth 'S' — offers three examples in order to convince us that there are situations in which individuals are neither accurately describable as believing that p or failing to so believe, but are rather in 'in-between states of belief'. He then argues that there are no 'Bayesian' or representational strategies for explicating these, and proposes a dispositional account. I do not have any fundamental objection to the idea that there might be 'in-between states of belief'. What I (...)
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  18. What are degrees of belief.Lina Eriksson & Alan Hájek - 2007 - Studia Logica 86 (2):185-215.
    Probabilism is committed to two theses: 1) Opinion comes in degrees—call them degrees of belief, or credences. 2) The degrees of belief of a rational agent obey the probability calculus. Correspondingly, a natural way to argue for probabilism is: i) to give an account of what degrees of belief are, and then ii) to show that those things should be probabilities, on pain of irrationality. Most of the action in the literature concerns stage ii). Assuming that stage i) has been (...)
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  19.  87
    Measuring the overall incoherence of credence functions.Julia Staffel - 2015 - Synthese 192 (5):1467-1493.
    Many philosophers hold that the probability axioms constitute norms of rationality governing degrees of belief. This view, known as subjective Bayesianism, has been widely criticized for being too idealized. It is claimed that the norms on degrees of belief postulated by subjective Bayesianism cannot be followed by human agents, and hence have no normative force for beings like us. This problem is especially pressing since the standard framework of subjective Bayesianism only allows us to distinguish between two kinds of credence (...)
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  20. Bayesian Epistemology.Stephan Hartmann & Jan Sprenger - 2010 - In Duncan Pritchard & Sven Bernecker (eds.), The Routledge Companion to Epistemology. London: Routledge. pp. 609-620.
    Bayesian epistemology addresses epistemological problems with the help of the mathematical theory of probability. It turns out that the probability calculus is especially suited to represent degrees of belief (credences) and to deal with questions of belief change, confirmation, evidence, justification, and coherence. Compared to the informal discussions in traditional epistemology, Bayesian epis- temology allows for a more precise and fine-grained analysis which takes the gradual aspects of these central epistemological notions into account. Bayesian epistemology therefore complements traditional epistemology; it (...)
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  21.  17
    Quitting Certainties: A Bayesian Framework Modeling Degrees of Belief, Michael G. Titelbaum. Oxford University Press, 2013, xii + 345 pages. [REVIEW]Alexandru Marcoci - 2015 - Economics and Philosophy 31 (1):194-200.
  22.  38
    Quitting Certainties: A Bayesian Framework Modeling Degrees of Belief, by Michael G. Titelbaum: Oxford: Oxford University Press, 2012, pp. xii + 345, £40.00. [REVIEW]Michael Levin - 2014 - Australasian Journal of Philosophy 92 (1):200-203.
  23.  38
    Introduction: Outright Belief and Degrees of Belief.Martin Smith Philip A. Ebert - 2012 - Dialectica 66 (3):305-308.
    What is the relation between ‘full’ or ‘outright’ belief and the various levels of confidence that agents can have in the propositions that concern them? This paper argues for a new answer to this question. Decision theory implies that in making decisions, rational agents must treat certain propositions as though they were completely certain; but on most forms of decision theory, these propositions are not ones for which any finite agent could have maximal justification – the agent will clearly have (...)
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  24. Bayesian Norms and Non-Ideal Agents.Julia Staffel - 2024 - In Maria Lasonen-Aarnio & Clayton Littlejohn (eds.), The Routledge Handbook of the Philosophy of Evidence. New York, NY: Routledge.
    Bayesian epistemology provides a popular and powerful framework for modeling rational norms on credences, including how rational agents should respond to evidence. The framework is built on the assumption that ideally rational agents have credences, or degrees of belief, that are representable by numbers that obey the axioms of probability. From there, further constraints are proposed regarding which credence assignments are rationally permissible, and how rational agents’ credences should change upon learning new evidence. While the details are hotly disputed, all (...)
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  25.  69
    MICHAEL G. TITELBAUM Quitting Certainties: A Bayesian Framework Modeling Degrees of Belief. [REVIEW]Alastair Wilson - 2014 - British Journal for the Philosophy of Science 65 (4):887-891.
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    Quitting Certainties: A Bayesian Framework Modeling Degrees of Belief. [REVIEW]Kenny Easwaran - 2016 - Philosophical Review 125 (1):143-148.
  27. Why Credences Are Not Beliefs.Elizabeth Jackson - 2022 - Australasian Journal of Philosophy 100 (2):360-370.
    A question of recent interest in epistemology and philosophy of mind is how belief and credence relate to each other. A number of philosophers argue for a belief-first view of the relationship between belief and credence. On the belief-first view, what it is to have a credence just is to have a particular kind of belief, that is, a belief whose content involves probabilities or epistemic modals. Here, I argue against the belief-first view: specifically, I argue that it cannot account (...)
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  28. Are Credences Different From Beliefs?Roger Clarke & Julia Staffel - forthcoming - In Ernest Sosa, Matthias Steup, John Turri & Blake Roeber (eds.), Contemporary Debates in Epistemology, 3rd edition. Wiley-Blackwell.
    This is a three-part exchange on the relationship between belief and credence. It begins with an opening essay by Roger Clarke that argues for the claim that the notion of credence generalizes the notion of belief. Julia Staffel argues in her reply that we need to distinguish between mental states and models representing them, and that this helps us explain what it could mean that belief is a special case of credence. Roger Clarke's final essay reflects on the compatibility of (...)
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  29. Classical versus Bayesian Statistics.Eric Johannesson - 2020 - Philosophy of Science 87 (2):302-318.
    In statistics, there are two main paradigms: classical and Bayesian statistics. The purpose of this article is to investigate the extent to which classicists and Bayesians can agree. My conclusion is that, in certain situations, they cannot. The upshot is that, if we assume that the classicist is not allowed to have a higher degree of belief in a null hypothesis after he has rejected it than before, then he has to either have trivial or incoherent credences to begin (...)
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  30. The Objects of Belief and Credence.David Braun - 2016 - Mind 125 (498):469-497.
    David Chalmers uses Bayesian theories of credence to argue against referentialism about belief. This paper argues that Chalmers’s Bayesian objections to referentialism are similar to older, more familiar objections to referentialism. There are familiar responses to the old objections, and there is a predictable way to modify those old responses to meet Chalmers’s Bayesian objections. The new responses to the new objections are no less plausible than the old responses to the old objections. Chalmers’s positive theory of belief and credence (...)
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  31. Self-Locating Credences.Michael G. Titelbaum - 2016 - In Alan Hájek & Christopher Hitchcock (eds.), The Oxford Handbook of Probability and Philosophy. Oxford: Oxford University Press.
    A plea: If you're going to propose a Bayesian framework for updating self-locating degrees of belief, please read this piece first. I've tried to survey all the extant formalisms, group them by their general approach, then describe challenges faced by every formalism employing a given approach. Hopefully this survey will prevent further instances of authors' re-inventing updating rules already proposed elsewhere in the literature.
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  32.  35
    A bayesian paradox.Ruth Weintraub - 2001 - British Journal for the Philosophy of Science 52 (1):51-66.
    A seemingly plausible application of Bayesian decision-theoretic reasoning to determine one's rational degrees of belief yields a paradoxical conclusion: one ought to jettison one's intermediate credences in favour of more extreme (opinionated) ones. I discuss various attempts to solve the paradox, those involving the acceptance of the paradoxical conclusion, and those which attempt to block its derivation.
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  33.  28
    Hyperintensional evidence and Bayesian coherence.Ted Poston - 2024 - Asian Journal of Philosophy 3 (1):1-13.
    Bayesian approaches to rationality require that a person’s degrees of belief be coherent. Among other implications, coherence requires that a person has the same degree of belief in every logically equivalent proposition. However, a person can have evidence for a claim without having evidence for all its propositional equivalences. This paper explores this conflict and argues that a person may be perfectly rational by virtue of responding to their evidence, even if their credences are not coherent. The paper also (...)
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  34. Disagreement, Credences, and Outright Belief.Michele Palmira - 2018 - Ratio 31 (2):179-196.
    This paper addresses a largely neglected question in ongoing debates over disagreement: what is the relation, if any, between disagreements involving credences and disagreements involving outright beliefs? The first part of the paper offers some desiderata for an adequate account of credal and full disagreement. The second part of the paper argues that both phenomena can be subsumed under a schematic definition which goes as follows: A and B disagree if and only if the accuracy conditions of A's doxastic attitude (...)
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  35. Bets on Hats: On Dutch Books Against Groups, Degrees of Belief as Betting Rates, and Group-Reflection.Luc Bovens & Wlodek Rabinowicz - 2011 - Episteme 8 (3):281-300.
    The Puzzle of the Hats is a puzzle in social epistemology. It describes a situation in which a group of rational agents with common priors and common goals seems vulnerable to a Dutch book if they are exposed to different information and make decisions independently. Situations in which this happens involve violations of what might be called the Group-Reflection Principle. As it turns out, the Dutch book is flawed. It is based on the betting interpretation of the subjective probabilities, but (...)
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  36. How to Be a Bayesian Dogmatist.Brian T. Miller - 2016 - Australasian Journal of Philosophy 94 (4):766-780.
    ABSTRACTRational agents have consistent beliefs. Bayesianism is a theory of consistency for partial belief states. Rational agents also respond appropriately to experience. Dogmatism is a theory of how to respond appropriately to experience. Hence, Dogmatism and Bayesianism are theories of two very different aspects of rationality. It's surprising, then, that in recent years it has become common to claim that Dogmatism and Bayesianism are jointly inconsistent: how can two independently consistent theories with distinct subject matter be jointly inconsistent? In this (...)
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  37. Troubles for Bayesian Formal Epistemology.Terry Horgan - 2017 - Res Philosophica 94 (2):1-23.
    I raise skeptical doubts about the prospects of Bayesian formal epistemology for providing an adequate general normative model of epistemic rationality. The notion of credence, I argue, embodies a very dubious psychological myth, viz., that for virtually any proposition p that one can entertain and understand, one has some quantitatively precise, 0-to-1 ratio-scale, doxastic attitude toward p. The concept of credence faces further serious problems as well—different ones depending on whether credence 1 is construed as full belief (the limit case (...)
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  38. Do beliefs supervene on degrees of confidence.Luc Bovens - 1999 - In Anthonie W. M. Meijers (ed.), Belief, Cognition, and the Will. Tilburg University Press. pp. 6--27.
    I examine the relationship between belief and credences and distinguish between a dogmatic, a Lockean, an agentic, and an abductive notion of belief. I conclude with some thoughts on voluntarism and evidentialism.
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  39. Degrees of Acceptance.Alexander Dinges - 2022 - Philosophical Quarterly (3):578-594.
    While many authors distinguish belief from acceptance, it seems almost universally agreed that no similar distinction can be drawn between degrees of belief, or credences, and degrees of acceptance. I challenge this assumption in this paper. Acceptance comes in degrees and acknowledging this helps to resolve problems in at least two philosophical domains. Degrees of acceptance play vital roles when we simplify our reasoning, and they ground the common ground of a conversation if we assume context probabilism, i.e., that the (...)
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  40. Partial Belief and Flat-out Belief.Keith Frankish - 2009 - In Franz Huber & Christoph Schmidt-Petri (eds.), Degrees of belief. London: Springer. pp. 75--93.
    There is a duality in our everyday view of belief. On the one hand, we sometimes speak of credence as a matter of degree. We talk of having some level of confidence in a claim (that a certain course of action is safe, for example, or that a desired event will occur) and explain our actions by reference to these degrees of confidence – tacitly appealing, it seems, to a probabilistic calculus such as that formalized in Bayesian decision theory. (...)
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  41. The crucial roles of biodiversity loss belief and perception in urban residents’ consumption attitude and behavior towards animal-based products.Nguyen Minh-Hoang, Tam-Tri Le, Thomas E. Jones & Quan-Hoang Vuong - manuscript
    Products made from animal fur and skin have been a major part of human civilization. However, in modern society, the unsustainable consumption of these products – often considered luxury goods – has many negative environmental impacts. This study explores how people’s perceptions of biodiversity affect their attitudes and behaviors toward consumption. To investigate the information process deeper, we add the moderation of beliefs about biodiversity loss. Following the Bayesian Mindsponge Framework (BMF) analytics, we use mindsponge-based reasoning for constructing conceptual models (...)
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  42. The crucial roles of biodiversity loss belief and perception in urban residents’ consumption attitude and behavior towards animal-based products.Minh-Hoang Nguyen, Tam-Tri Le, Thomas Jones & Quan-Hoang Vuong - manuscript
    Products made from animal fur and skin have been a major part of human civilization. However, in modern society, the unsustainable consumption of these products – often considered luxury goods – has many negative environmental impacts. This study explores how people’s perceptions of biodiversity affect their attitudes and behaviors toward consumption. To investigate the information process deeper, we add the moderation of beliefs about biodiversity loss. Following the Bayesian Mindsponge Framework (BMF) analytics, we use mindsponge-based reasoning for constructing conceptual models (...)
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  43. Dr. Truthlove or: How I Learned to Stop Worrying and Love Bayesian Probabilities.Kenny Easwaran - 2016 - Noûs 50 (4):816-853.
    Many philosophers have argued that "degree of belief" or "credence" is a more fundamental state grounding belief. Many other philosophers have been skeptical about the notion of "degree of belief", and take belief to be the only meaningful notion in the vicinity. This paper shows that one can take belief to be fundamental, and ground a notion of "degree of belief" in the patterns of belief, assuming that an agent has a collection of beliefs that isn't dominated (...)
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  44. The degree of epistemic justification and the conjunction fallacy.Tomoji Shogenji - 2012 - Synthese 184 (1):29-48.
    This paper describes a formal measure of epistemic justification motivated by the dual goal of cognition, which is to increase true beliefs and reduce false beliefs. From this perspective the degree of epistemic justification should not be the conditional probability of the proposition given the evidence, as it is commonly thought. It should be determined instead by the combination of the conditional probability and the prior probability. This is also true of the degree of incremental confirmation, and I (...)
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  45. Belief, credence, and norms.Lara Buchak - 2014 - Philosophical Studies 169 (2):1-27.
    There are currently two robust traditions in philosophy dealing with doxastic attitudes: the tradition that is concerned primarily with all-or-nothing belief, and the tradition that is concerned primarily with degree of belief or credence. This paper concerns the relationship between belief and credence for a rational agent, and is directed at those who may have hoped that the notion of belief can either be reduced to credence or eliminated altogether when characterizing the norms governing ideally rational agents. It presents (...)
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  46.  60
    Simple belief.John Collins - 2020 - Synthese 197 (11):4867-4885.
    We have reasons to want an epistemology of simple belief in addition to the Bayesian notion of belief which admits of degree. Accounts of simple belief which attempt to reduce it to the notion of credence all face difficulties. We argue that each conception captures an important aspect of our pre-theoretic thinking about epistemology; the differences between the two accounts of belief stem from two different conceptions of unlikelihood. On the one hand there is unlikelihood in the sense of (...)
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  47. Accuracy, Risk, and the Principle of Indifference.Richard Pettigrew - 2016 - Philosophy and Phenomenological Research 92 (1):35-59.
    In Bayesian epistemology, the problem of the priors is this: How should we set our credences (or degrees of belief) in the absence of evidence? That is, how should we set our prior or initial credences, the credences with which we begin our credal life? David Lewis liked to call an agent at the beginning of her credal journey a superbaby. The problem of the priors asks for the norms that govern these superbabies. -/- The Principle of Indifference gives a (...)
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  48. Perception and Disjunctive Belief: A New Problem for Ambitious Predictive Processing.Assaf Weksler - forthcoming - Australasian Journal of Philosophy.
    Perception can’t have disjunctive content. Whereas you can think that a box is blue or red, you can’t see a box as being blue or red. Based on this fact, I develop a new problem for the ambitious predictive processing theory, on which the brain is a machine for minimizing prediction error, which approximately implements Bayesian inference. I describe a simple case of updating a disjunctive belief given perceptual experience of one of the disjuncts, in which Bayesian inference and (...)
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  49.  65
    A dilemma for the imprecise bayesian.Namjoong Kim - 2016 - Synthese 193 (6):1681-1702.
    Many philosophers regard the imprecise credence framework as a more realistic model of probabilistic inferences with imperfect empirical information than the traditional precise credence framework. Hence, it is surprising that the literature lacks any discussion on how to update one’s imprecise credences when the given evidence itself is imprecise. To fill this gap, I consider two updating principles. Unfortunately, each of them faces a serious problem. The first updating principle, which I call “generalized conditionalization,” sometimes forces an agent to change (...)
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  50. Credence: A Belief-First Approach.Andrew Moon & Elizabeth Jackson - 2020 - Canadian Journal of Philosophy 50 (5):652–669.
    This paper explains and defends a belief-first view of the relationship between belief and credence. On this view, credences are a species of beliefs, and the degree of credence is determined by the content of what is believed. We begin by developing what we take to be the most plausible belief-first view. Then, we offer several arguments for it. Finally, we show how it can resist objections that have been raised to belief-first views. We conclude that the belief-first view (...)
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