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  1. Logic for equivocators.David Lewis - 1982 - Noûs 16 (3):431-441.
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  • Truth and probability.Frank Ramsey - 2010 - In Antony Eagle (ed.), Philosophy of Probability: Contemporary Readings. New York: Routledge. pp. 52-94.
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  • Probability and Partial Belief.Frank Plumpton Ramsey - 1961 - In John Langshaw Austin (ed.), Philosophical Papers. Oxford, England: Clarendon Press. pp. 95-96.
    This note is a postscript to Ramsey's 'Truth and Probability'. It replaces that article's psychological reading of subjective probability with a reading of it as a consistency condition on the theory that we act to maximise expected utility.
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  • Avoiding Dutch Books despite inconsistent credences.Alexander R. Pruss - 2020 - Synthese 198 (12):11265-11289.
    It is often loosely said that Ramsey The foundations of mathematics and other logical essays, Routledge and Kegan Paul, Abingdon, pp 156–198, 1931) and de Finetti Studies in subjective probability, Kreiger Publishing, Huntington, 1937) proved that if your credences are inconsistent, then you will be willing to accept a Dutch Book, a wager portfolio that is sure to result in a loss. Of course, their theorems are true, but the claim about acceptance of Dutch Books assumes a particular method of (...)
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  • Theories of Probability.Terrence Fine - 1973 - Academic Press.
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  • The value of truth: a reply to Howson.James M. Joyce - 2015 - Analysis 75 (3):413-424.
    Colin Howson has recently argued that accuracy arguments for probabilism fail because they assume a privileged ‘coding’ in which TRUE is assigned the value 1 and FALSE is assigned the value 0. I explain why this is wrong by first showing that Howson’s objections are based on a misconception about the way in which degrees of confidence are measured, and then reformulating the accuracy argument in a way that manifestly does not depend on the coding of truth-values. Along the way, (...)
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  • The Axioms of Subjective Probability.Peter C. Fishburn - 1986 - Statistical Science 1 (3):335-358.
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  • Subjective Probabilities Should be Sharp.Adam Elga - 2010 - Philosophers' Imprint 10.
    Many have claimed that unspecific evidence sometimes demands unsharp, indeterminate, imprecise, vague, or interval-valued probabilities. Against this, a variant of the diachronic Dutch Book argument shows that perfectly rational agents always have perfectly sharp probabilities.
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  • Representation theorems and realism about degrees of belief.Lyle Zynda - 2000 - Philosophy of Science 67 (1):45-69.
    The representation theorems of expected utility theory show that having certain types of preferences is both necessary and sufficient for being representable as having subjective probabilities. However, unless the expected utility framework is simply assumed, such preferences are also consistent with being representable as having degrees of belief that do not obey the laws of probability. This fact shows that being representable as having subjective probabilities is not necessarily the same as having subjective probabilities. Probabilism can be defended on the (...)
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  • Games, Beliefs and Credences.Brian Weatherson - 2014 - Philosophy and Phenomenological Research 92 (2):209-236.
    In previous work I’ve defended an interest-relative theory of belief. This paper continues the defence. It has four aims. -/- 1. To offer a new kind of reason for being unsatis ed with the simple Lockean reduction of belief to credence. 2. To defend the legitimacy of appealing to credences in a theory of belief. 3. To illustrate the importance of theoretical, as well as practical, interests in an interest-relative account of belief. 4. To revise my account to cover propositions (...)
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  • Support theory: A nonextensional representation of subjective probability.Amos Tversky & Derek J. Koehler - 1994 - Psychological Review 101 (4):547-567.
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  • Necessary and sufficient conditions for existence of a unique measure strictly agreeing with a qualitative probability ordering.Patrick Suppes & Mario Zanotti - 1976 - Journal of Philosophical Logic 5 (3):431 - 438.
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  • What is "real" in Probabilism?H. Orri Stefánsson - 2017 - Australasian Journal of Philosophy 95 (3):573-587.
    This paper defends two related claims about belief. First, the claim that unlike numerical degrees of belief, comparative beliefs are primitive and psychologically real. Second, the claim that the fundamental norm of Probabilism is not that numerical degrees of belief should satisfy the probability axioms, but rather that comparative beliefs should satisfy certain constraints.
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  • On the Ratio Challenge for Comparativism.H. Orri Stefánsson - 2018 - Australasian Journal of Philosophy 96 (2):380-390.
    This paper discusses a challenge for Comparativists about belief, who hold that numerical degree of belief (in particular, subjective probability) is a useful fiction, unlike comparative belief, which they regard as real. The challenge is to make sense of claims like ‘I am twice as confident in A as in B’ in terms of comparative belief only. After showing that at least some Comparativists can meet this challenge, I discuss implications for Zynda’s [2000] and Stefánsson’s [2017] defences of Comparativism.
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  • The Foundations of Mathematics and other Logical Essays.Frank Plumpton Ramsey, R. B. Braithwaite & G. E. Moore - 1931 - Mind 40 (160):476-482.
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  • Prospectism and the weak money pump argument.Martin Peterson - 2015 - Theory and Decision 78 (3):451-456.
    Hare proposes a view he calls prospectism for making choices in situations in which preferences have a common, but problematic structure. I show that prospectism permits the decision-maker to make a series of choices she knows in advance will lead to a sure loss. I also argue that a theory that permits the decision-maker to make choices she knows in advance will lead to a sure loss should be rejected.
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  • On the nature of the conjunction fallacy.Rodrigo Moro - 2009 - Synthese 171 (1):1 - 24.
    In a seminal work, Tversky and Kahneman showed that in some contexts people tend to believe that a conjunction of events (e.g., Linda is a bank teller and is active in the feminist movement) is more likely to occur than one of the conjuncts (e.g., Linda is a bank teller). This belief violates the conjunction rule in probability theory. Tversky and Kahneman called this phenomenon the “conjunction fallacy”. Since the discovery of the phenomenon in 1983, researchers in psychology and philosophy (...)
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  • Representation theorems and the foundations of decision theory.Christopher J. G. Meacham & Jonathan Weisberg - 2011 - Australasian Journal of Philosophy 89 (4):641 - 663.
    Representation theorems are often taken to provide the foundations for decision theory. First, they are taken to characterize degrees of belief and utilities. Second, they are taken to justify two fundamental rules of rationality: that we should have probabilistic degrees of belief and that we should act as expected utility maximizers. We argue that representation theorems cannot serve either of these foundational purposes, and that recent attempts to defend the foundational importance of representation theorems are unsuccessful. As a result, we (...)
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  • Attitudes de dicto and de se.David Lewis - 1979 - Philosophical Review 88 (4):513-543.
    I hear the patter of little feet around the house, I expect Bruce. What I expect is a cat, a particular cat. If I heard such a patter in another house, I might expect a cat but no particular cat. What I expect then seems to be a Meinongian incomplete cat. I expect winter, expect stormy weather, expect to shovel snow, expect fatigue---a season, a phenomenon, an activity, a state. I expect that someday mankind will inhabit at least five planets. (...)
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  • The Foundations of Causal Decision Theory.Isaac Levi & James M. Joyce - 2000 - Journal of Philosophy 97 (7):387.
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  • The Axioms and Algebra of Intuitive Probability.B. O. Koopman - 1940 - Journal of Symbolic Logic 5 (4):153-154.
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  • The Foundations of Causal Decision Theory.James M. Joyce - 1999 - Cambridge University Press.
    This book defends the view that any adequate account of rational decision making must take a decision maker's beliefs about causal relations into account. The early chapters of the book introduce the non-specialist to the rudiments of expected utility theory. The major technical advance offered by the book is a 'representation theorem' that shows that both causal decision theory and its main rival, Richard Jeffrey's logic of decision, are both instances of a more general conditional decision theory. The book solves (...)
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  • A defense of imprecise credences in inference and decision making1.James M. Joyce - 2010 - Philosophical Perspectives 24 (1):281-323.
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  • The foundations of causal decision theory. [REVIEW]Mirek Janusz - 2001 - Philosophical Review 110 (2):296-300.
    This book makes a significant contribution to the standard decision theory, that is, the theory of choice built around the principle of maximizing expected utility, both to its causal version and to the more traditional noncausal approach. The author’s success in clarifying the foundations of the standard decision theory in general, and causal decision theory in particular, also makes the book uniquely suitable for a person whose research in philosophy has led her to want to learn about contemporary decision theory. (...)
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  • 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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  • Dealing with logical omniscience: Expressiveness and pragmatics.Joseph Y. Halpern & Riccardo Pucella - 2011 - Artificial Intelligence 175 (1):220-235.
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  • 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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  • Ramsey without Ethical Neutrality: A New Representation Theorem.Edward Elliott - 2017 - Mind 126 (501):1-51.
    Frank Ramsey's ‘Truth and Probability’ sketches a proposal for the empirical measurement of credences, along with a corresponding set of axioms for a representation theorem intended to characterize the preference conditions under which this measurement process is applicable. There are several features of Ramsey's formal system which make it attractive and worth developing. However, in specifying his measurement process and his axioms, Ramsey introduces the notion of an ethically neutral proposition, the assumed existence of which plays a key role throughout (...)
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  • ‘Ramseyfying’ Probabilistic Comparativism.Edward Elliott - 2020 - Philosophy of Science 87 (4):727-754.
    Comparativism is the view that comparative confidences (e.g., being more confident that P than that Q) are more fundamental than degrees of belief (e.g., believing that P with some strength x). In this paper, I outline the basis for a new, non-probabilistic version of comparativism inspired by a suggestion made by Frank Ramsey in `Probability and Partial Belief'. I show how, and to what extent, `Ramseyan comparativism' might be used to weaken the (unrealistically strong) probabilistic coherence conditions that comparativism traditionally (...)
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  • Impossible worlds and partial belief.Edward Elliott - 2019 - Synthese 196 (8):3433-3458.
    One response to the problem of logical omniscience in standard possible worlds models of belief is to extend the space of worlds so as to include impossible worlds. It is natural to think that essentially the same strategy can be applied to probabilistic models of partial belief, for which parallel problems also arise. In this paper, I note a difficulty with the inclusion of impossible worlds into probabilistic models. Under weak assumptions about the space of worlds, most of the propositions (...)
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  • Betting against the Zen Monk: on preferences and partial belief.Edward Elliott - 2019 - Synthese 198 (4):3733-3758.
    According to the preference-centric approach to understanding partial belief, the connection between partial beliefs and preferences is key to understanding what partial beliefs are and how they’re measured. As Ramsey put it, the ‘degree of a belief is a causal property of it, which we can express vaguely as the extent to which we are prepared to act on it’ The Foundations of Mathematics and Other Logical Essays, Routledge, Oxon, pp 156–198, 1931). But this idea is not as popular as (...)
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  • A Representation Theorem for Frequently Irrational Agents.Edward Elliott - 2017 - Journal of Philosophical Logic 46 (5):467-506.
    The standard representation theorem for expected utility theory tells us that if a subject’s preferences conform to certain axioms, then she can be represented as maximising her expected utility given a particular set of credences and utilities—and, moreover, that having those credences and utilities is the only way that she could be maximising her expected utility. However, the kinds of agents these theorems seem apt to tell us anything about are highly idealised, being always probabilistically coherent with infinitely precise degrees (...)
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  • Putting Logic in Its Place: Formal Constraints on Rational Belief.Henry E. Kyburg - 2005 - Bulletin of Symbolic Logic 11 (4):534-535.
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  • The nature of epistemic space.David J. Chalmers - 2011 - In Andy Egan & Brian Weatherson (eds.), Epistemic Modality. Oxford University Press.
    A natural way to think about epistemic possibility is as follows. When it is epistemically possible (for a subject) that p, there is an epistemically possible scenario (for that subject) in which p. The epistemic scenarios together constitute epistemic space. It is surprisingly difficult to make the intuitive picture precise. What sort of possibilities are we dealing with here? In particular, what is a scenario? And what is the relationship between scenarios and items of knowledge and belief? This chapter tries (...)
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  • The imaginary fundamentalists: The unshocking truth about Bayesian cognitive science.Nick Chater, Noah Goodman, Thomas L. Griffiths, Charles Kemp, Mike Oaksford & Joshua B. Tenenbaum - 2011 - Behavioral and Brain Sciences 34 (4):194-196.
    If Bayesian Fundamentalism existed, Jones & Love's (J&L's) arguments would provide a necessary corrective. But it does not. Bayesian cognitive science is deeply concerned with characterizing algorithms and representations, and, ultimately, implementations in neural circuits; it pays close attention to environmental structure and the constraints of behavioral data, when available; and it rigorously compares multiple models, both within and across papers. J&L's recommendation of Bayesian Enlightenment corresponds to past, present, and, we hope, future practice in Bayesian cognitive science.
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  • Problems in Epistemic Space.Jens Christian Bjerring - 2012 - Journal of Philosophical Logic 43 (1):153-170.
    When a proposition might be the case, for all an agent knows, we can say that the proposition is epistemically possible for the agent. In the standard possible worlds framework, we analyze modal claims using quantification over possible worlds. It is natural to expect that something similar can be done for modal claims involving epistemic possibility. The main aim of this paper is to investigate the prospects of constructing a space of worlds—epistemic space—that allows us to model what is epistemically (...)
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  • Granularity problems.Jens Christian Bjerring & Wolfgang Schwarz - 2017 - Philosophical Quarterly 67 (266):22-37.
    Possible-worlds accounts of mental or linguistic content are often criticized for being too coarse-grained. To make room for more fine-grained distinctions among contents, several authors have recently proposed extending the space of possible worlds by "impossible worlds". We argue that this strategy comes with serious costs: we would effectively have to abandon most of the features that make the possible-worlds framework attractive. More generally, we argue that while there are intuitive and theoretical considerations against overly coarse-grained notions of content, the (...)
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  • The Foundations of Statistics.Leonard J. Savage - 1954 - Wiley Publications in Statistics.
    Classic analysis of the subject and the development of personal probability; one of the greatest controversies in modern statistcal thought.
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  • Mad pain and Martian pain.David Lewis - 1980 - In Ned Block (ed.), Readings in the Philosophy of Psychology. Harvard University Press. pp. 216-222.
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  • Putting Logic in Its Place. Formal Constraints on Rational Belief.David Christensen - 2007 - Erkenntnis 67 (1):143-146.
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  • The Foundations of Statistics.Leonard J. Savage - 1954 - Synthese 11 (1):86-89.
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  • Prospect Theory: An Analysis of Decision Under Risk.D. Kahneman & A. Tversky - 1979 - Econometrica: Journal of the Econometric Society:263--291.
    The following values have no corresponding Zotero field: PB - JSTOR.
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  • Subjective Probability and Expected Utility without Additivity.David Schmeidler - 1989 - Econometrica 57:571-589.
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  • Putting Logic in Its Place. Formal Constraints on Rational Belief.David Christensen - 2008 - Critica 40 (120):141-148.
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  • The Foundations of Statistics.Leonard J. Savage - 1956 - Philosophy of Science 23 (2):166-166.
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  • 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 sketch (...)
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  • Sul Significato Soggettivo della Probabilittextà.Bruno De Finetti - 1931 - Fundamenta Mathematicae 17:298--329.
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  • A Treatise on Probability.J. M. Keynes - 1989 - British Journal for the Philosophy of Science 40 (2):219-222.
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  • A treatise on probability.J. Keynes - 1924 - Revue de Métaphysique et de Morale 31 (1):11-12.
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  • The Axioms and Algebra of Intuitive Probability.Bernard O. Koopman - 1940 - Annals of Mathematics:269--292.
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