Results for 'Bayesian decision theory'

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  1. Bayesian Decision Theory and Stochastic Independence.Philippe Mongin - 2020 - Philosophy of Science 87 (1):152-178.
    As stochastic independence is essential to the mathematical development of probability theory, it seems that any foundational work on probability should be able to account for this property. Bayesian decision theory appears to be wanting in this respect. Savage’s postulates on preferences under uncertainty entail a subjective expected utility representation, and this asserts only the existence and uniqueness of a subjective probability measure, regardless of its properties. What is missing is a preference condition corresponding to stochastic (...)
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  2. Bayesian Decision Theory and Stochastic Independence.Philippe Mongin - 2017 - TARK 2017.
    Stochastic independence has a complex status in probability theory. It is not part of the definition of a probability measure, but it is nonetheless an essential property for the mathematical development of this theory. Bayesian decision theorists such as Savage can be criticized for being silent about stochastic independence. From their current preference axioms, they can derive no more than the definitional properties of a probability measure. In a new framework of twofold uncertainty, we introduce preference (...)
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  3. Decision Theory: Yes! Truth Conditions: No!Nate Charlow - 2016 - In Nate Charlow Matthew Chrisman (ed.), Deontic Modality. Oxford University Press.
    This essay makes the case for, in the phrase of Angelika Kratzer, packing the fruits of the study of rational decision-making into our semantics for deontic modals—specifically, for parametrizing the truth-condition of a deontic modal to things like decision problems and decision theories. Then it knocks it down. While the fundamental relation of the semantic theory must relate deontic modals to things like decision problems and theories, this semantic relation cannot be intelligibly understood as representing (...)
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  4. Decision Theory, Intelligent Planning and Counterfactuals.Michael John Shaffer - 2008 - Minds and Machines 19 (1):61-92.
    The ontology of decision theory has been subject to considerable debate in the past, and discussion of just how we ought to view decision problems has revealed more than one interesting problem, as well as suggested some novel modifications of classical decision theory. In this paper it will be argued that Bayesian, or evidential, decision-theoretic characterizations of decision situations fail to adequately account for knowledge concerning the causal connections between acts, states, and (...)
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  5. A Simpler and More Realistic Subjective Decision Theory.Haim Gaifman & Yang Liu - 2018 - Synthese 195 (10):4205--4241.
    In his classic book “the Foundations of Statistics” Savage developed a formal system of rational decision making. The system is based on (i) a set of possible states of the world, (ii) a set of consequences, (iii) a set of acts, which are functions from states to consequences, and (iv) a preference relation over the acts, which represents the preferences of an idealized rational agent. The goal and the culmination of the enterprise is a representation theorem: Any preference relation (...)
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  6. Bayesian Cognitive Science, Unification, and Explanation.Stephan Hartmann & Matteo Colombo - 2017 - British Journal for the Philosophy of Science 68 (2).
    It is often claimed that the greatest value of the Bayesian framework in cognitive science consists in its unifying power. Several Bayesian cognitive scientists assume that unification is obviously linked to explanatory power. But this link is not obvious, as unification in science is a heterogeneous notion, which may have little to do with explanation. While a crucial feature of most adequate explanations in cognitive science is that they reveal aspects of the causal mechanism that produces the phenomenon (...)
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  7. Incomplete Preference and Indeterminate Comparative Probability.Yang Liu - forthcoming - British Journal for the Philosophy of Science:axaa009.
    The notion of comparative probability defined in Bayesian subjectivist theory stems from an intuitive idea that, for a given pair of events, one event may be considered “more probable” than the other. Yet it is conceivable that there are cases where it is indeterminate as to which event is more probable, due to, e.g., lack of robust statistical information. We take that these cases involve indeterminate comparative probabilities. This paper provides a Savage-style decision-theoretic foundation for indeterminate comparative (...)
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  8. Fragmentation and Logical Omniscience.Adam Elga & Agustin Rayo - forthcoming - Noûs.
    It would be good to have a Bayesian decision theory that assesses our decisions and thinking according to everyday standards of rationality — standards that do not require logical omniscience (Garber 1983, Hacking 1967). To that end we develop a “fragmented” decision theory in which a single state of mind is represented by a family of credence functions, each associated with a distinct choice condition (Lewis 1982, Stalnaker 1984). The theory imposes a local coherence (...)
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  9. A Comprehensive Theory of Induction and Abstraction, Part I.Cael L. Hasse -
    I present a solution to the epistemological or characterisation problem of induction. In part I, Bayesian Confirmation Theory (BCT) is discussed as a good contender for such a solution but with a fundamental explanatory gap (along with other well discussed problems); useful assigned probabilities like priors require substantive degrees of belief about the world. I assert that one does not have such substantive information about the world. Consequently, an explanation is needed for how one can be licensed to (...)
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  10. A Dual Approach to Bayesian Inference and Adaptive Control.Leigh Tesfatsion - 1982 - Theory and Decision 14 (2):177-194.
    Probability updating via Bayes' rule often entails extensive informational and computational requirements. In consequence, relatively few practical applications of Bayesian adaptive control techniques have been attempted. This paper discusses an alternative approach to adaptive control, Bayesian in spirit, which shifts attention from the updating of probability distributions via transitional probability assessments to the direct updating of the criterion function, itself, via transitional utility assessments. Results are illustrated in terms of an adaptive reinvestment two-armed bandit problem.
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  11. Homeostatic Epistemology : Reliability, Coherence and Coordination in a Bayesian Virtue Epistemology.Susannah Kate Devitt - 2013 - Dissertation,
    How do agents with limited cognitive capacities flourish in informationally impoverished or unexpected circumstances? Aristotle argued that human flourishing emerged from knowing about the world and our place within it. If he is right, then the virtuous processes that produce knowledge, best explain flourishing. Influenced by Aristotle, virtue epistemology defends an analysis of knowledge where beliefs are evaluated for their truth and the intellectual virtue or competences relied on in their creation. However, human flourishing may emerge from how degrees of (...)
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  12. Causal Decision Theory and Decision Instability.Brad Armendt - 2019 - Journal of Philosophy 116 (5):263-277.
    The problem of the man who met death in Damascus appeared in the infancy of the theory of rational choice known as causal decision theory. A straightforward, unadorned version of causal decision theory is presented here and applied, along with Brian Skyrms’ deliberation dynamics, to Death in Damascus and similar problems. Decision instability is a fascinating topic, but not a source of difficulty for causal decision theory. Andy Egan’s purported counterexample to causal (...)
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  13. Tournament Decision Theory.Abelard Podgorski - 2022 - Noûs 56 (1):176-203.
    The dispute in philosophical decision theory between causalists and evidentialists remains unsettled. Many are attracted to the causal view’s endorsement of a species of dominance reasoning, and to the intuitive verdicts it gets on a range of cases with the structure of the infamous Newcomb’s Problem. But it also faces a rising wave of purported counterexamples and theoretical challenges. In this paper I will describe a novel decision theory which saves what is appealing about the causal (...)
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  14. Decision Theory.Lara Buchak - 2016 - In Christopher Hitchcock & Alan Hajek (eds.), The Oxford Handbook of Probability and Philosophy. Oxford University Press.
    Decision theory has at its core a set of mathematical theorems that connect rational preferences to functions with certain structural properties. The components of these theorems, as well as their bearing on questions surrounding rationality, can be interpreted in a variety of ways. Philosophy’s current interest in decision theory represents a convergence of two very different lines of thought, one concerned with the question of how one ought to act, and the other concerned with the question (...)
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  15. Decision Theory for Agents with Incomplete Preferences.Adam Bales, Daniel Cohen & Toby Handfield - 2014 - Australasian Journal of Philosophy 92 (3):453-70.
    Orthodox decision theory gives no advice to agents who hold two goods to be incommensurate in value because such agents will have incomplete preferences. According to standard treatments, rationality requires complete preferences, so such agents are irrational. Experience shows, however, that incomplete preferences are ubiquitous in ordinary life. In this paper, we aim to do two things: (1) show that there is a good case for revising decision theory so as to allow it to apply non-vacuously (...)
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  16. Causal Decision Theory: A Counterexample.Arif Ahmed - 2013 - Philosophical Review 122 (2):289-306.
    The essay presents a novel counterexample to Causal Decision Theory (CDT). Its interest is that it generates a case in which CDT violates the very principles that motivated it in the first place. The essay argues that the objection applies to all extant formulations of CDT and that the only way out for that theory is a modification of it that entails incompatibilism. The essay invites the reader to find this consequence of CDT a reason to reject (...)
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  17. Countable Additivity, Idealization, and Conceptual Realism.Yang Liu - 2020 - Economics and Philosophy 36 (1):127-147.
    This paper addresses the issue of finite versus countable additivity in Bayesian probability and decision theory -- in particular, Savage's theory of subjective expected utility and personal probability. I show that Savage's reason for not requiring countable additivity in his theory is inconclusive. The assessment leads to an analysis of various highly idealised assumptions commonly adopted in Bayesian theory, where I argue that a healthy dose of, what I call, conceptual realism is often (...)
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  18. Statistical Inference and the Plethora of Probability Paradigms: A Principled Pluralism.Mark L. Taper, Gordon Brittan Jr & Prasanta S. Bandyopadhyay - manuscript
    The major competing statistical paradigms share a common remarkable but unremarked thread: in many of their inferential applications, different probability interpretations are combined. How this plays out in different theories of inference depends on the type of question asked. We distinguish four question types: confirmation, evidence, decision, and prediction. We show that Bayesian confirmation theory mixes what are intuitively “subjective” and “objective” interpretations of probability, whereas the likelihood-based account of evidence melds three conceptions of what constitutes an (...)
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  19. What Does Decision Theory Have to Do with Wanting?Milo Phillips-Brown - 2021 - Mind 130 (518):413-437.
    Decision theory and folk psychology both purport to represent the same phenomena: our belief-like and desire- and preference-like states. They also purport to do the same work with these representations: explain and predict our actions. But they do so with different sets of concepts. There's much at stake in whether one of these two sets of concepts can be accounted for with the other. Without such an account, we'd have two competing representations and systems of prediction and explanation, (...)
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  20. The Sure-Thing Principle and P2.Yang Liu - 2017 - Economics Letters 159:221-223.
    This paper offers a fine analysis of different versions of the well known sure-thing principle. We show that Savage's formal formulation of the principle, i.e., his second postulate (P2), is strictly stronger than what is intended originally.
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  21. Normative Decision Theory.Edward Elliott - 2019 - Analysis 79 (4):755-772.
    A review of some major topics of debate in normative decision theory from circa 2007 to 2019. Topics discussed include the ongoing debate between causal and evidential decision theory, decision instability, risk-weighted expected utility theory, decision-making with incomplete preferences, and decision-making with imprecise credences.
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  22. Belief gambles in epistemic decision theory.Mattias Skipper - 2021 - Philosophical Studies 178 (2):407-426.
    Don’t form beliefs on the basis of coin flips or random guesses. More generally, don’t take belief gambles: if a proposition is no more likely to be true than false given your total body of evidence, don’t go ahead and believe that proposition. Few would deny this seemingly innocuous piece of epistemic advice. But what, exactly, is wrong with taking belief gambles? Philosophers have debated versions of this question at least since the classic dispute between William Clifford and William James (...)
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  23. Low Attention Impairs Optimal Incorporation of Prior Knowledge in Perceptual Decisions.Jorge Morales, Guillermo Solovey, Brian Maniscalco, Dobromir Rahnev, Floris P. de Lange & Hakwan Lau - 2015 - Attention, Perception, and Psychophysics 77 (6):2021-2036.
    When visual attention is directed away from a stimulus, neural processing is weak and strength and precision of sensory data decreases. From a computational perspective, in such situations observers should give more weight to prior expectations in order to behave optimally during a discrimination task. Here we test a signal detection theoretic model that counter-intuitively predicts subjects will do just the opposite in a discrimination task with two stimuli, one attended and one unattended: when subjects are probed to discriminate the (...)
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    Wishing, Decision Theory, and Two-Dimensional Content.Kyle H. Blumberg - forthcoming - Journal of Philosophy.
    This paper is about two requirements on wish reports whose interaction motivates a novel semantics for these ascriptions. The first requirement concerns the ambiguities that arise when determiner phrases, e.g. definite descriptions, interact with `wish'. More specifically, several theorists have recently argued that attitude ascriptions featuring counterfactual attitude verbs license interpretations on which the determiner phrase is interpreted relative to the subject's beliefs. The second requirement involves the fact that desire reports in general require decision-theoretic notions for their analysis. (...)
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  25. Decision Theory.Johanna Thoma - 2019 - In Richard Pettigrew & Jonathan Weisberg (eds.), The Open Handbook of Formal Epistemology. PhilPapers Foundation. pp. 57-106.
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  26. An Argument Against Causal Decision Theory.Jack Spencer - 2021 - Analysis 81 (1):52-61.
    This paper develops an argument against causal decision theory. I formulate a principle of preference, which I call the Guaranteed Principle. I argue that the preferences of rational agents satisfy the Guaranteed Principle, that the preferences of agents who embody causal decision theory do not, and hence that causal decision theory is false.
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  27. A Conditional Expected Utility Model for Myopic Decision Makers.Leigh Tesfatsion - 1980 - Theory and Decision 12 (2):185-206.
    An expected utility model of individual choice is formulated which allows the decision maker to specify his available actions in the form of controls (partial contingency plans) and to simultaneously choose goals and controls in end-mean pairs. It is shown that the Savage expected utility model, the Marschak- Radner team model, the Bayesian statistical decision model, and the standard optimal control model can be viewed as special cases of this goal-control expected utility model.
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  28. Epistemic Decision Theory's Reckoning.Conor Mayo-Wilson & Gregory Wheeler - manuscript
    Epistemic decision theory (EDT) employs the mathematical tools of rational choice theory to justify epistemic norms, including probabilism, conditionalization, and the Principal Principle, among others. Practitioners of EDT endorse two theses: (1) epistemic value is distinct from subjective preference, and (2) belief and epistemic value can be numerically quantified. We argue the first thesis, which we call epistemic puritanism, undermines the second.
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  29. 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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  30. How Did That Individual Make That Perceptual Decision?David A. Booth - 2018 - Behavioral and Brain Sciences 41:E226.
    Suboptimality of decision making needs no explanation. High level accounts of suboptimality in diverse tasks cannot add up to a mechanistic theory of perceptual decision making. Mental processes operate on the contents of information brought by the experimenter and the participant to the task, not on the amount of information in the stimuli without regard to physical and social context.
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  31. Success-First Decision Theories.Preston Greene - 2018 - In Arif Ahmed (ed.), Newcomb's Problem. Cambridge University Press. pp. 115–137.
    The standard formulation of Newcomb's problem compares evidential and causal conceptions of expected utility, with those maximizing evidential expected utility tending to end up far richer. Thus, in a world in which agents face Newcomb problems, the evidential decision theorist might ask the causal decision theorist: "if you're so smart, why ain’cha rich?” Ultimately, however, the expected riches of evidential decision theorists in Newcomb problems do not vindicate their theory, because their success does not generalize. Consider (...)
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  32. Causal Decision Theory and EPR Correlations.Arif Ahmed & Adam Caulton - 2014 - Synthese 191 (18):4315-4352.
    The paper argues that on three out of eight possible hypotheses about the EPR experiment we can construct novel and realistic decision problems on which (a) Causal Decision Theory and Evidential Decision Theory conflict (b) Causal Decision Theory and the EPR statistics conflict. We infer that anyone who fully accepts any of these three hypotheses has strong reasons to reject Causal Decision Theory. Finally, we extend the original construction to show that (...)
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  33. Transformative Experience and Decision Theory.Richard Pettigrew - 2015 - Philosophy and Phenomenological Research 91 (3):766-774.
    This paper is part of a book symposium for L. A. Paul (2014) Transformative Experience (OUP).
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  34. Law-Abiding Causal Decision Theory.Timothy Luke Williamson & Alexander Sandgren - forthcoming - British Journal for the Philosophy of Science.
    In this paper we discuss how Causal Decision Theory should be modified to handle a class of problematic cases involving deterministic laws. Causal Decision Theory, as it stands, is problematically biased against your endorsing deterministic propositions (for example it tells you to deny Newtonian physics, regardless of how confident you are of its truth). Our response is that this is not a problem for Causal Decision Theory per se, but arises because of the standard (...)
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  35. A Foundation for Causal Decision Theory.Brad Armendt - 1986 - Topoi 5 (1):3-19.
    The primary aim of this paper is the presentation of a foundation for causal decision theory. This is worth doing because causal decision theory (CDT) is philosophically the most adequate rational decision theory now available. I will not defend that claim here by elaborate comparison of the theory with all its competitors, but by providing the foundation. This puts the theory on an equal footing with competitors for which foundations have already been (...)
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  36. Why Be Random?Thomas Icard - 2021 - Mind 130 (517):fzz065.
    When does it make sense to act randomly? A persuasive argument from Bayesian decision theory legitimizes randomization essentially only in tie-breaking situations. Rational behaviour in humans, non-human animals, and artificial agents, however, often seems indeterminate, even random. Moreover, rationales for randomized acts have been offered in a number of disciplines, including game theory, experimental design, and machine learning. A common way of accommodating some of these observations is by appeal to a decision-maker’s bounded computational resources. (...)
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  37. Decision Theory, Philosophical Perspectives.Darren Bradley - 2013 - In Hal Pashler (ed.), Encyclopedia of the Mind. Sage Publications.
    Decision theory is concerned with how agents should act when the consequences of their actions are uncertain. The central principle of contemporary decision theory is that the rational choice is the choice that maximizes subjective expected utility. This entry explains what this means, and discusses the philosophical motivations and consequences of the theory. The entry will consider some of the main problems and paradoxes that decision theory faces, and some of responses that can (...)
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  38. Is There a Place in Bayesian Confirmation Theory for the Reverse Matthew Effect?William Roche - 2018 - Synthese 195 (4):1631-1648.
    Bayesian confirmation theory is rife with confirmation measures. Many of them differ from each other in important respects. It turns out, though, that all the standard confirmation measures in the literature run counter to the so-called “Reverse Matthew Effect” (“RME” for short). Suppose, to illustrate, that H1 and H2 are equally successful in predicting E in that p(E | H1)/p(E) = p(E | H2)/p(E) > 1. Suppose, further, that initially H1 is less probable than H2 in that p(H1) (...)
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  39. Philosophy as Conceptual Engineering: Inductive Logic in Rudolf Carnap's Scientific Philosophy.Christopher F. French - 2015 - Dissertation, University of British Columbia
    My dissertation explores the ways in which Rudolf Carnap sought to make philosophy scientific by further developing recent interpretive efforts to explain Carnap’s mature philosophical work as a form of engineering. It does this by looking in detail at his philosophical practice in his most sustained mature project, his work on pure and applied inductive logic. I, first, specify the sort of engineering Carnap is engaged in as involving an engineering design problem and then draw out the complications of design (...)
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  40. What Decision Theory Provides the Best Procedure for Identifying the Best Action Available to a Given Artificially Intelligent System?Samuel A. Barnett - 2018 - Dissertation, University of Oxford
    Decision theory has had a long-standing history in the behavioural and social sciences as a tool for constructing good approximations of human behaviour. Yet as artificially intelligent systems (AIs) grow in intellectual capacity and eventually outpace humans, decision theory becomes evermore important as a model of AI behaviour. What sort of decision procedure might an AI employ? In this work, I propose that policy-based causal decision theory (PCDT), which places a primacy on the (...)
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  41. Subjective Probabilities Need Not Be Sharp.Jake Chandler - 2014 - Erkenntnis 79 (6):1273-1286.
    It is well known that classical, aka ‘sharp’, Bayesian decision theory, which models belief states as single probability functions, faces a number of serious difficulties with respect to its handling of agnosticism. These difficulties have led to the increasing popularity of so-called ‘imprecise’ models of decision-making, which represent belief states as sets of probability functions. In a recent paper, however, Adam Elga has argued in favour of a putative normative principle of sequential choice that he claims (...)
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  42. Explanatoriness is Evidentially Irrelevant, or Inference to the Best Explanation Meets Bayesian Confirmation Theory.W. Roche & E. Sober - 2013 - Analysis 73 (4):659-668.
    In the world of philosophy of science, the dominant theory of confirmation is Bayesian. In the wider philosophical world, the idea of inference to the best explanation exerts a considerable influence. Here we place the two worlds in collision, using Bayesian confirmation theory to argue that explanatoriness is evidentially irrelevant.
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  43. Heart of DARCness.Yang Liu & Huw Price - 2019 - Australasian Journal of Philosophy 97 (1):136-150.
    There is a long-standing disagreement in the philosophy of probability and Bayesian decision theory about whether an agent can hold a meaningful credence about an upcoming action, while she deliberates about what to do. Can she believe that it is, say, 70% probable that she will do A, while she chooses whether to do A? No, say some philosophers, for Deliberation Crowds Out Prediction (DCOP), but others disagree. In this paper, we propose a valid core for DCOP, (...)
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  44. Risk Attitudes in Axiomatic Decision Theory: A Conceptual Perspective.Jean Baccelli - 2018 - Theory and Decision 84 (1):61-82.
    In this paper, I examine the decision-theoretic status of risk attitudes. I start by providing evidence showing that the risk attitude concepts do not play a major role in the axiomatic analysis of the classic models of decision-making under risk. This can be interpreted as reflecting the neutrality of these models between the possible risk attitudes. My central claim, however, is that such neutrality needs to be qualified and the axiomatic relevance of risk attitudes needs to be re-evaluated (...)
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  45. Decision Theory, Symmetry and Causal Structure: Reply to Meacham and Weisberg.Michael Clark & Nicholas Shackel - 2003 - Mind 112 (448):691-701.
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  46. Do We Really Need a Knowledge-Based Decision Theory?Davide Fassio & Jie Gao - 2021 - Synthese 199 (3-4):7031-7059.
    The paper investigates what type of motivation can be given for adopting a knowledge-based decision theory. KBDT seems to have several advantages over competing theories of rationality. It is commonly argued that this theory would naturally fit with the intuitive idea that being rational is doing what we take to be best given what we know, an idea often supported by appeal to ordinary folk appraisals. Moreover, KBDT seems to strike a perfect balance between the problematic extremes (...)
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  47. An Externalist Decision Theory for a Pragmatic Epistemology.Brian Kim - 2019 - In Pragmatic Encroachment in Epistemology. Routledge.
    In recent years, some epistemologists have argued that practical factors can make the difference between knowledge and mere true belief. While proponents of this pragmatic thesis have proposed necessary and sufficient conditions for knowledge, it is striking that they have failed to address Gettier cases. As a result, the proposed analyses of knowledge are either lacking explanatory power or susceptible to counterexamples. Gettier cases are also worth reflecting on because they raise foundational questions for the pragmatist. Underlying these challenges is (...)
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  48. Decision Theory.Ben Eggleston - 2017 - In Sacha Golub & Jens Timmermann (eds.), The Cambridge History of Moral Philosophy. pp. 706-717.
    A book chapter (about 4,000 words, plus references) on decision theory in moral philosophy, with particular attention to uses of decision theory in specifying the contents of moral principles (e.g., expected-value forms of act and rule utilitarianism), uses of decision theory in arguing in support of moral principles (e.g., the hypothetical-choice arguments of Harsanyi and Rawls), and attempts to derive morality from rationality (e.g., the views of Gauthier and McClennen).
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  49. Advice for the Steady: Decision Theory and the Requirements of Instrumental Rationality.Johanna Thoma - 2017 - Dissertation,
    Standard decision theory, or rational choice theory, is often interpreted to be a theory of instrumental rationality. This dissertation argues, however, that the core requirements of orthodox decision theory cannot be defended as general requirements of instrumental rationality. Instead, I argue that these requirements can only be instrumentally justified to agents who have a desire to have choice dispositions that are stable over time and across different choice contexts. Past attempts at making instrumentalist arguments (...)
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  50. Conditionals in Causal Decision Theory.John Cantwell - 2013 - Synthese 190 (4):661-679.
    This paper explores the possibility that causal decision theory can be formulated in terms of probabilities of conditionals. It is argued that a generalized Stalnaker semantics in combination with an underlying branching time structure not only provides the basis for a plausible account of the semantics of indicative conditionals, but also that the resulting conditionals have properties that make them well-suited as a basis for formulating causal decision theory. Decision theory (at least if we (...)
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