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  1. 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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  • 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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  • 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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  • 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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  • Games, Beliefs and Credences.Brian Weatherson - 2016 - 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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  • 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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  • A Defense of Imprecise Credences in Inference and Decision Making1.James M. Joyce - 2010 - Philosophical Perspectives 24 (1):281-323.
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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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  • 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 Foundations of Causal Decision Theory.Isaac Levi & James M. Joyce - 2000 - Journal of Philosophy 97 (7):387.
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  • The Axioms of Subjective Probability.Peter C. Fishburn - 1986 - Statistical Science 1 (3):335-358.
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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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  • Troubles for Bayesian Formal Epistemology.Terry Horgan - 2017 - Res Philosophica 94 (2):233-255.
    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 or instead is (...)
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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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  • 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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  • Truth and Probability.F. Ramsey - 1926 - In Antony Eagle (ed.), Philosophy of Probability: Contemporary Readings. Routledge. pp. 52-94.
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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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  • Attitudes de Dicto and de Se.David Lewis - 1979 - Philosophical Review 88 (4):513-543.
    t f 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 (...)
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  • Logic for Equivocators.David K. Lewis - 1982 - Noûs 16 (3):431-441.
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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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  • Theories of Probability.Terence L. Fine - 1973 - Academic Press.
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  • Sul Significato Soggettivo della Probabilittextà.Bruno De Finetti - 1931 - Fundamenta Mathematicae 17:298--329.
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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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  • 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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  • Probability and Partial Belief.Frank Plumpton Ramsey - 1929 - In Frank Ramsey (ed.), Philosophical Papers. Cambridge University 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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  • Putting Logic in Its Place. Formal Constraints on Rational Belief.David Christensen - 2008 - Critica 40 (120):141-148.
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  • The Axioms and Algebra of Intuitive Probability.Bernard O. Koopman - 1940 - Annals of Mathematics:269--292.
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