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  1. Counterfactuals.David K. Lewis - 1973 - Malden, Mass.: Blackwell.
    Counterfactuals is David Lewis' forceful presentation of and sustained argument for a particular view about propositions which express contrary to fact conditionals, including his famous defense of realism about possible worlds and his theory of laws of nature.
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  • (2 other versions)Counterfactuals.David Lewis - 1973 - Tijdschrift Voor Filosofie 36 (3):602-605.
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  • (2 other versions)Counterfactuals.David Lewis - 1973 - Foundations of Language 13 (1):145-151.
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  • (2 other versions)Counterfactuals.David Lewis - 1973 - Philosophy of Science 42 (3):341-344.
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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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  • Statistical Reasoning with Imprecise Probabilities.Peter Walley - 1991 - Chapman & Hall.
    An examination of topics involved in statistical reasoning with imprecise probabilities. The book discusses assessment and elicitation, extensions, envelopes and decisions, the importance of imprecision, conditional previsions and coherent statistical models.
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  • Decision Theory with a Human Face.Richard Bradley - 2017 - Cambridge University Press.
    When making decisions, people naturally face uncertainty about the potential consequences of their actions due in part to limits in their capacity to represent, evaluate or deliberate. Nonetheless, they aim to make the best decisions possible. In Decision Theory with a Human Face, Richard Bradley develops new theories of agency and rational decision-making, offering guidance on how 'real' agents who are aware of their bounds should represent the uncertainty they face, how they should revise their opinions as a result of (...)
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  • Philosophical Theories of Probability.Donald Gillies - 2000 - New York: Routledge.
    The Twentieth Century has seen a dramatic rise in the use of probability and statistics in almost all fields of research. This has stimulated many new philosophical ideas on probability. _Philosophical Theories of Probability_ is the first book to present a clear, comprehensive and systematic account of these various theories and to explain how they relate to one another. Gillies also offers a distinctive version of the propensity theory of probability, and the intersubjective interpretation, which develops the subjective theory.
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  • (1 other version)Evidential Symmetry and Mushy Credence.Roger White - 2009 - Oxford Studies in Epistemology 3:161-186.
    the symmetry of our evidential situation. If our confidence is best modeled by a standard probability function this means that we are to distribute our subjective probability or credence sharply and evenly over possibilities among which our evidence does not discriminate. Once thought to be the central principle of probabilistic reasoning by great..
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  • (1 other version)On indeterminate probabilities.Isaac Levi - 1974 - Journal of Philosophy 71 (13):391-418.
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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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  • A defense of imprecise credences in inference and decision making.James Joyce - 2010 - Philosophical Perspectives 24 (1):281-323.
    Some Bayesians have suggested that beliefs based on ambiguous or incomplete evidence are best represented by families of probability functions. I spend the first half of this essay outlining one version of this imprecise model of belief, and spend the second half defending the model against recent objections, raised by Roger White and others, which concern the phenomenon of probabilistic dilation. Dilation occurs when learning some definite fact forces a person’s beliefs about an event to shift from a sharp, point-valued (...)
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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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  • (1 other version)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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  • Decision-Making Under Indeterminacy.J. Robert G. Williams - 2014 - Philosophers' Imprint 14.
    Decisions are made under uncertainty when there are distinct outcomes of a given action, and one is uncertain to which the act will lead. Decisions are made under indeterminacy when there are distinct outcomes of a given action, and it is indeterminate to which the act will lead. This paper develops a theory of (synchronic and diachronic) decision-making under indeterminacy that portrays the rational response to such situations as inconstant. Rational agents have to capriciously and randomly choose how to resolve (...)
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  • How Degrees of Belief Reflect Evidence.James M. Joyce - 2005 - Philosophical Perspectives 19 (1):153-179.
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  • Choice and chance.Brian Skyrms - 1966 - Belmont, Calif.,: Dickenson Pub. Co..
    This definitive survey of the hottest issues in inductive logic sets the stage for further classroom discussion.
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  • (1 other version)On Indeterminate Probabilities.Isaac Levi - 1978 - Journal of Philosophy 71 (13):233--261.
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  • (1 other version)Evidential Symmetry and Mushy Credence.Roger White - 2005 - In Tamar Szabó Gendler & John Hawthorne (eds.), Oxford Studies in Epistemology. Oxford University Press. pp. 161-186.
    the symmetry of our evidential situation. If our confidence is best modeled by a standard probability function this means that we are to distribute our subjective probability or credence sharply and evenly over possibilities among which our evidence does not discriminate. Once thought to be the central principle of probabilistic reasoning by great..
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  • Bayesianism With A Human Face.Richard C. Jeffrey - 1983 - In John Earman (ed.), Testing Scientific Theories. Minneapolis: University of Minnesota Press. pp. 133--156.
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  • Maxmin expected utility with non-unique prior.Itzhak Gilboa & David Schmeidler - 1989 - Journal of Mathematical Economics 18 (2):141–53.
    Acts are functions from states of nature into finite-support distributions over a set of ‘deterministic outcomes’. We characterize preference relations over acts which have a numerical representation by the functional J(f)=min>∫u∘ f dP¦PϵC where f is an act, u is a von Neumann-Morgenstern utility over outcomes, and C is a closed and convex set of finitely additive probability measures on the states of nature. In addition to the usual assumptions on the preference relation as transitivity, completeness, continuity and monotonicity, we (...)
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  • Demystifying Dilation.Arthur Paul Pedersen & Gregory Wheeler - 2014 - Erkenntnis 79 (6):1305-1342.
    Dilation occurs when an interval probability estimate of some event E is properly included in the interval probability estimate of E conditional on every event F of some partition, which means that one’s initial estimate of E becomes less precise no matter how an experiment turns out. Critics maintain that dilation is a pathological feature of imprecise probability models, while others have thought the problem is with Bayesian updating. However, two points are often overlooked: (1) knowing that E is stochastically (...)
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  • (1 other version)Unreliable probabilities, risk taking, and decision making.Peter Gärdenfors & Nils-Eric Sahlin - 1982 - Synthese 53 (3):361-386.
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  • (1 other version)Confidence and Coarse-Grained Attitudes.Scott Sturgeon - 2010 - Oxford Studies in Epistemology 3.
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  • (1 other version)Confidence and coarse-grained attitudes.Scott Sturgeon - 2005 - In Tamar Szabó Gendler & John Hawthorne (eds.), Oxford Studies in Epistemology. Oxford University Press. pp. 3--126.
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  • Imprecise Probabilities and Unstable Betting Behaviour.Anna Mahtani - 2014 - 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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  • Decision making with imprecise probabilities.Brian Weatherson - 1998
    Orthodox Bayesian decision theory requires an agent’s beliefs representable by a real-valued function, ideally a probability function. Many theorists have argued this is too restrictive; it can be perfectly reasonable to have indeterminate degrees of belief. So doxastic states are ideally representable by a set of probability functions. One consequence of this is that the expected value of a gamble will be imprecise. This paper looks at the attempts to extend Bayesian decision theory to deal with such cases, and concludes (...)
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  • Revising incomplete attitudes.Richard Bradley - 2009 - Synthese 171 (2):235 - 256.
    Bayesian models typically assume that agents are rational, logically omniscient and opinionated. The last of these has little descriptive or normative appeal, however, and limits our ability to describe how agents make up their minds (as opposed to changing them) or how they can suspend or withdraw their opinions. To address these limitations this paper represents the attitudinal states of non-opinionated agents by sets of (permissible) probability and desirability functions. Several basic ways in which such states of mind can be (...)
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  • Intuitive Dilation?Casey Hart & Michael G. Titelbaum - 2015 - Thought: A Journal of Philosophy 4 (4):252-262.
    Roger White objects to interval-valued credence theories because they produce a counterintuitive “dilation” effect in a story he calls the Coin Game. We respond that results in the Coin Game were bound to be counterintuitive anyway, because the story involves an agent who learns a biconditional. Biconditional updates produce surprising results whether the credences involved are ranged or precise, so White's story is no counterexample to ranged credence theories.
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  • (1 other version)Counterfactuals. [REVIEW]William Parry - 1973 - Journal of Symbolic Logic 44 (2):278-281.
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  • Orderly Decision Theory.Peter J. Hammond - 1988 - Economics and Philosophy 4 (2):292-297.
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  • Safeguards of a Disunified Mind.Wlodek Rabinowicz - 2014 - Inquiry: An Interdisciplinary Journal of Philosophy 57 (3):356-383.
    The papers focuses on pragmatic arguments for various rationality constraints on a decision maker’s state of mind: on her beliefs or preferences. An argument of this kind typically targets constraint violations. It purports to show that a violator of a given constraint can be confronted with a decision problem in which she will act to her guaranteed disadvantage. Dramatically put, she can be exploited by a clever bookie who doesn’t know more than the agent herself. Examples of pragmatic arguments of (...)
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  • (1 other version)The judicial decision.[author unknown] - 1962 - Philosophical Books 3 (1):21-23.
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