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  1. Theory of Games and Economic Behavior.John Von Neumann & Oskar Morgenstern - 1944 - Princeton, NJ, USA: Princeton University Press.
    This is the classic work upon which modern-day game theory is based. What began as a modest proposal that a mathematician and an economist write a short paper together blossomed, when Princeton University Press published Theory of Games and Economic Behavior. In it, John von Neumann and Oskar Morgenstern conceived a groundbreaking mathematical theory of economic and social organization, based on a theory of games of strategy. Not only would this revolutionize economics, but the entirely new field of scientific inquiry (...)
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  • (1 other version)The Foundations of Statistics.Leonard J. Savage - 1954 - Synthese 11 (1):86-89.
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  • Theory of Games and Economic Behavior.John von Neumann & Oskar Morgenstern - 1944 - Science and Society 9 (4):366-369.
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  • (1 other version)The Foundations of Statistics.Leonard J. Savage - 1956 - Philosophy of Science 23 (2):166-166.
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  • 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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  • 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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  • Decision theory and folk psychology.Philip Pettit - 1991 - In Michael Bacharach & Susan Hurley (eds.), Essays in the Foundations of Decision Theory. Blackwell. pp. 147-175.
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  • Foundations of Measurement, Vol. I: Additive and Polynomial Representations.David Krantz, Duncan Luce, Patrick Suppes & Amos Tversky (eds.) - 1971 - New York Academic Press.
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  • The Foundations of Statistics.Leonard 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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  • Representation theorems and the foundations of decision theory.Christopher 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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  • Frege’s Puzzle and the Objects of Credence.David J. Chalmers - 2011 - Mind 120 (479):587-635.
    The objects of credence are the entities to which credences are assigned for the purposes of a successful theory of credence. I use cases akin to Frege's puzzle to argue against referentialism about credence : the view that objects of credence are determined by the objects and properties at which one's credence is directed. I go on to develop a non-referential account of the objects of credence in terms of sets of epistemically possible scenarios.
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  • The Logic of Decision.Richard C. Jeffrey - 1965 - New York, NY, USA: University of Chicago Press.
    "[This book] proposes new foundations for the Bayesian principle of rational action, and goes on to develop a new logic of desirability and probabtility."—Frederic Schick, _Journal of Philosophy_.
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  • A contrast between two decision rules for use with (convex) sets of probabilities: Γ-maximin versus e-admissibilty.T. Seidenfeld - 2004 - Synthese 140 (1-2):69 - 88.
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  • (1 other version)The structure and content of truth.Donald Davidson - 1990 - Journal of Philosophy 87 (6):279-328.
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  • (1 other version)The nature of epistemic space.David J. Chalmers - 2011 - In Andy Egan & Brian Weatherson (eds.), Epistemic Modality. Oxford, GB: 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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  • Risk and Rationality.Lara Buchak - 2013 - Oxford, GB: Oxford University Press.
    Lara Buchak sets out a new account of rational decision-making in the face of risk. She argues that the orthodox view is too narrow, and suggests an alternative, more permissive theory: one that allows individuals to pay attention to the worst-case or best-case scenario, and vindicates the ordinary decision-maker.
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  • Subjective expected utility: A review of normative theories. [REVIEW]Peter C. Fishburn - 1981 - Theory and Decision 13 (2):139-199.
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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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  • Decision Theory without Representation Theorems.Kenny Easwaran - 2014 - Philosophers' Imprint 14.
    Naive versions of decision theory take probabilities and utilities as primitive and use expected value to give norms on rational decision. However, standard decision theory takes rational preference as primitive and uses it to construct probability and utility. This paper shows how to justify a version of the naive theory, by taking dominance as the most basic normatively required preference relation, and then extending it by various conditions under which agents should be indifferent between acts. The resulting theory can make (...)
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  • Ramsey and the measurement of belief.Richard Bradley - 2001 - In David Corfield & Jon Williamson (eds.), Foundations of Bayesianism. Kluwer Academic Publishers.
    Foundations of Bayesianism is an authoritative collection of papers addressing the key challenges that face the Bayesian interpretation of probability today. Some of these papers seek to clarify the relationships between Bayesian, causal and logical reasoning. Others consider the application of Bayesianism to artificial intelligence, decision theory, statistics and the philosophy of science and mathematics. The volume includes important criticisms of Bayesian reasoning and also gives an insight into some of the points of disagreement amongst advocates of the Bayesian approach. (...)
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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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  • 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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  • (1 other version)Radical interpretation.David K. Lewis - 1974 - Synthese 23 (July-August):331-344.
    What knowledge would suffice to yield an interpretation of an arbitrary utterance of a language when such knowledge is based on evidence plausibly available to a nonspeaker of that language? it is argued that it is enough to know a theory of truth for the language and that the theory satisfies tarski's 'convention t' and that it gives an optimal fit to data about sentences held true, Under specified conditions, By native speakers.
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  • Toward a unified theory of meaning and action.Donald Davidson - 1980 - Grazer Philosophische Studien 11 (1):1-12.
    The central propositional attitudes of belief, desire, and meaning are interdependent; it is therefore fruitless to analyse one or two of them in terms of the others. A method is outlined in this paper that yields a theory for interpreting speech, a measure of degree of belief, and a measure of desirability. The method combines in a novel way features of Bayesean decision theory, and a Quinean approach to radical interpretation.
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  • Betting on Theories.Patrick Maher - 1993 - Cambridge, New York and Melbourne: Cambridge University Press.
    This book is a major contribution to decision theory, focusing on the question of when it is rational to accept scientific theories. The author examines both Bayesian decision theory and confirmation theory, refining and elaborating the views of Ramsey and Savage. He argues that the most solid foundation for confirmation theory is to be found in decision theory, and he provides a decision-theoretic derivation of principles for how many probabilities should be revised over time. Professor Maher defines a notion of (...)
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  • State-Dependent Utilities.Mark J. Schervish, Teddy Seidenfeld & Joseph B. Kadane - unknown
    Several axiom systems for preference among acts lead to a unique probability and a state-independent utility such that acts are ranked according to their expected utilities. These axioms have been used as a foundation for Bayesian decision theory and subjective probability calculus. In this article we note that the uniqueness of the probability is relative to the choice of whatcounts as a constant outcome. Although it is sometimes clear what should be considered constant, in many cases there are several possible (...)
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  • Realistic Decision Theory: Rules for Nonideal Agents in Nonideal Circumstances.Paul Weirich - 2004 - New York, US: OUP Usa.
    Decision theory aims at a general account of rationality covering humans but to begin makes idealizations about decision problems and agents' resources and circumstances. It treats inerrant agents with unlimited cognitive power facing tractable decision problems. This book systematically rolls back idealizations and without loss of precision treats errant agents with limited cognitive abilities facing decision problems without a stable top option. It recommends choices that maximize utility using quantizations of beliefs and desires in cases where probabilities and utilities are (...)
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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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  • (1 other version)Rational Decision and Causality.Ellery Eells - 1982 - Cambridge University Press.
    In past years, the traditional Bayesian theory of rational decision making, based on subjective calculations of expected utility, has faced powerful attack from philosophers such as David Lewis and Brian Skyrms, who advance an alternative causal decision theory. The test they present for the Bayesian is exemplified in the decision problem known as 'Newcomb's paradox' and in related decision problems and is held to support the prescriptions of the causal theory. As well as his conclusions, the concepts and methods of (...)
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  • Depragmatized dutch book arguments.Patrick Maher - 1997 - Philosophy of Science 64 (2):291-305.
    Recently a number of authors have tried to avoid the failures of traditional Dutch book arguments by separating them from pragmatic concerns of avoiding a sure loss. In this paper I examine defenses of this kind by Howson and Urbach, Hellman, and Christensen. I construct rigorous explications of their arguments and show that they are not cogent. I advocate abandoning Dutch book arguments in favor of a representation theorem.
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  • Probabilism, Representation Theorems, and Whether Deliberation Crowds Out Prediction.Edward Elliott - 2017 - Erkenntnis 82 (2):379-399.
    Decision-theoretic representation theorems have been developed and appealed to in the service of two important philosophical projects: in attempts to characterise credences in terms of preferences, and in arguments for probabilism. Theorems developed within the formal framework that Savage developed have played an especially prominent role here. I argue that the use of these ‘Savagean’ theorems create significant difficulties for both projects, but particularly the latter. The origin of the problem directly relates to the question of whether we can have (...)
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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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  • Representation theorems and the semantics of decision-theoretic concepts.Mikaël Cozic & Brian Hill - 2015 - Journal of Economic Methodology 22 (3):292-311.
    Contemporary decision theory places crucial emphasis on a family of mathematical results called representation theorems, which relate criteria for evaluating the available options to axioms pertaining to the decision-maker’s preferences. Various claims have been made concerning the reasons for the importance of these results. The goal of this article is to assess their semantic role: representation theorems are purported to provide definitions of the decision-theoretic concepts involved in the evaluation criteria. In particular, this claim shall be examined from the perspective (...)
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  • Value Relations Revisited.Wlodek Rabinowicz - 2012 - Economics and Philosophy 28 (2):133-164.
    In Rabinowicz (2008), I considered how value relations can best be analysed in terms of fitting pro-attitudes. In the formal model of that paper, fitting pro-attitudes are represented by the class of permissible preference orderings on a domain of items that are being compared. As it turns out, this approach opens up for a multiplicity of different types of value relationships, along with the standard relations of ‘better’, ‘worse’, ‘equally as good as’ and ‘incomparable in value’. Unfortunately, the approach is (...)
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  • (1 other version)Rational Decision and Causality.Ellery Eells - 2009 - Cambridge University Press.
    First published in 1982, Ellery Eells' original work on rational decision making had extensive implications for probability theorists, economists, statisticians and psychologists concerned with decision making and the employment of Bayesian principles. His analysis of the philosophical and psychological significance of Bayesian decision theories, causal decision theories and Newcomb's paradox continues to be influential in philosophy of science. His book is now revived for a new generation of readers and presented in a fresh twenty-first-century series livery, including a specially commissioned (...)
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  • On the Composition of Risk Preference and Belief.Peter P. Wakker - 2004 - Psychological Review 111 (1):236-241.
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  • The Logic of Decision.Henry E. Kyburg - 1968 - Philosophical Review 77 (2):250.
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  • Rational Decision and Causality by Ellery Eells. [REVIEW]James Cargile - 1984 - Journal of Philosophy 81 (3):163-168.
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