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  1. Jeffrey conditionalization: proceed with caution.Borut Trpin - 2020 - Philosophical Studies 177 (10):2985-3012.
    It has been argued that if the rigidity condition is satisfied, a rational agent operating with uncertain evidence should update her subjective probabilities by Jeffrey conditionalization or else a series of bets resulting in a sure loss could be made against her. We show, however, that even if the rigidity condition is satisfied, it is not always safe to update probability distributions by JC because there exist such sequences of non-misleading uncertain observations where it may be foreseen that an agent (...)
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  • Nonrational Belief Paradoxes as Byzantine Failures.Ryan Miller - manuscript
    David Christensen and others argue that Dutch Strategies are more like peer disagreements than Dutch Books, and should not count against agents’ conformity to ideal rationality. I review these arguments, then show that Dutch Books, Dutch Strategies, and peer disagreements are only possible in the case of what computer scientists call Byzantine Failures—uncorrected Byzantine Faults which update arbitrary values. Yet such Byzantine Failures make agents equally vulnerable to all three kinds of epistemic inconsistencies, so there is no principled basis for (...)
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  • Feminist Philosophy of Science1.Lynn Hankinson Nelson - 2002 - In Peter Machamer Michael Silberstein (ed.), The Blackwell Guide to the Philosophy of Science. Blackwell. pp. 312.
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  • Diachronic Dutch Books and Evidential Import.J. Dmitri Gallow - 2019 - Philosophy and Phenomenological Research 99 (1):49-80.
    A handful of well-known arguments (the 'diachronic Dutch book arguments') rely upon theorems establishing that, in certain circumstances, you are immune from sure monetary loss (you are not 'diachronically Dutch bookable') if and only if you adopt the strategy of conditionalizing (or Jeffrey conditionalizing) on whatever evidence you happen to receive. These theorems require non-trivial assumptions about which evidence you might acquire---in the case of conditionalization, the assumption is that, if you might learn that e, then it is not the (...)
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  • The Kinematics of Belief and Desire.Richard Bradley - 2007 - Synthese 156 (3):513-535.
    Richard Jeffrey regarded the version of Bayesian decision theory he floated in ‘The Logic of Decision’ and the idea of a probability kinematics—a generalisation of Bayesian conditioning to contexts in which the evidence is ‘uncertain’—as his two most important contributions to philosophy. This paper aims to connect them by developing kinematical models for the study of preference change and practical deliberation. Preference change is treated in a manner analogous to Jeffrey’s handling of belief change: not as mechanical outputs of combinations (...)
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  • Dynamic Coherence and Probability Kinematics.Brian Skyrms - 1987 - Philosophy of Science 54 (1):1-20.
    The question of coherence of rules for changing degrees of belief in the light of new evidence is studied, with special attention being given to cases in which evidence is uncertain. Belief change by the rule of conditionalization on an appropriate proposition and belief change by "probability kinematics" on an appropriate partition are shown to have like status.
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  • Bayesian Conditionalization and Probability Kinematics.Colin Howson & Allan Franklin - 1994 - British Journal for the Philosophy of Science 45 (2):451-466.
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  • Theories of Probability.Colin Howson - 1995 - British Journal for the Philosophy of Science 46 (1):1-32.
    My title is intended to recall Terence Fine's excellent survey, Theories of Probability [1973]. I shall consider some developments that have occurred in the intervening years, and try to place some of the theories he discussed in what is now a slightly longer perspective. Completeness is not something one can reasonably hope to achieve in a journal article, and any selection is bound to reflect a view of what is salient. In a subject as prone to dispute as this, there (...)
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  • Diachronic Rationality.Patrick Maher - 1992 - Philosophy of Science 59 (1):120-141.
    This is an essay in the Bayesian theory of how opinions should be revised over time. It begins with a discussion of the principle that van Fraassen has dubbed "Reflection". This principle is not a requirement of rationality; a diachronic Dutch argument, that purports to show the contrary, is fallacious. But under suitable conditions, it is irrational to actually implement shifts in probability that violate Reflection. Conditionalization and probability kinematics are special cases of the principle not to implement shifts that (...)
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  • The Consistency Argument for Ranking Functions.Franz Huber - 2007 - Studia Logica 86 (2):299-329.
    The paper provides an argument for the thesis that an agent’s degrees of disbelief should obey the ranking calculus. This Consistency Argument is based on the Consistency Theorem. The latter says that an agent’s belief set is and will always be consistent and deductively closed iff her degrees of entrenchment satisfy the ranking axioms and are updated according to the ranktheoretic update rules.
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  • Radical Probabilism and Bayesian Conditioning.Richard Bradley - 2005 - Philosophy of Science 72 (2):342-364.
    Richard Jeffrey espoused an antifoundationalist variant of Bayesian thinking that he termed ‘Radical Probabilism’. Radical Probabilism denies both the existence of an ideal, unbiased starting point for our attempts to learn about the world and the dogma of classical Bayesianism that the only justified change of belief is one based on the learning of certainties. Probabilistic judgment is basic and irreducible. Bayesian conditioning is appropriate when interaction with the environment yields new certainty of belief in some proposition but leaves one’s (...)
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  • Belief and Degrees of Belief.Franz Huber - 2009 - In F. Huber & C. Schmidt-Petri (eds.), Degrees of Belief. Springer.
    Degrees of belief are familiar to all of us. Our confidence in the truth of some propositions is higher than our confidence in the truth of other propositions. We are pretty confident that our computers will boot when we push their power button, but we are much more confident that the sun will rise tomorrow. Degrees of belief formally represent the strength with which we believe the truth of various propositions. The higher an agent’s degree of belief for a particular (...)
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  • Inference to the Best Explanation in Uncertain Evidential Situations.Borut Trpin & Max Pellert - 2019 - British Journal for the Philosophy of Science 70 (4):977-1001.
    It has recently been argued that a non-Bayesian probabilistic version of inference to the best explanation (IBE*) has a number of advantages over Bayesian conditionalization (Douven [2013]; Douven and Wenmackers [2017]). We investigate how IBE* could be generalized to uncertain evidential situations and formulate a novel updating rule IBE**. We then inspect how it performs in comparison to its Bayesian counterpart, Jeffrey conditionalization (JC), in a number of simulations where two agents, each updating by IBE** and JC, respectively, try to (...)
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  • Formal Representations of Belief.Franz Huber - 2008 - Stanford Encyclopedia of Philosophy.
    Epistemology is the study of knowledge and justified belief. Belief is thus central to epistemology. It comes in a qualitative form, as when Sophia believes that Vienna is the capital of Austria, and a quantitative form, as when Sophia's degree of belief that Vienna is the capital of Austria is at least twice her degree of belief that tomorrow it will be sunny in Vienna. Formal epistemology, as opposed to mainstream epistemology (Hendricks 2006), is epistemology done in a formal way, (...)
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  • Dutch Book Arguments.Susan Vineberg - 2011 - Stanford Encyclopedia of Philosophy.
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  • Maximum Entropy Inference as a Special Case of Conditionalization.Brian Skyrms - 1985 - Synthese 63 (1):55 - 74.
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  • Dynamic Inference and Everyday Conditional Reasoning in the New Paradigm.Mike Oaksford & Nick Chater - 2013 - Thinking and Reasoning 19 (3-4):346-379.
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  • On the Significance of Conditional Probabilities.Jordan Howard Sobel - 1996 - Synthese 109 (3):311 - 344.
    The orthodoxy that conditional probabilities reflect what are for a subject evidential bearings is seconded. This significance suggests that there should be principles equating rationally revised probabilities on new information with probabilities reached by conditionalizing on this information. Several principles, two of which are endorsed, are considered. A book is made against a violator of these, and it is argued that there must be something wrong with a person against whom such books can be made. Appendices comment on Popper-functions, elaborate (...)
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  • Subjective Probability and its Dynamics.Alan Hajek & Julia Staffel - forthcoming - In Markus Knauff & Wolfgang Spohn (eds.), MIT Handbook of Rationality. MIT Press.
    This chapter is a philosophical survey of some leading approaches in formal epistemology in the so-called ‘Bayesian’ tradition. According to them, a rational agent’s degrees of belief—credences—at a time are representable with probability functions. We also canvas various further putative ‘synchronic’ rationality norms on credences. We then consider ‘diachronic’ norms that are thought to constrain how credences should respond to evidence. We discuss some of the main lines of recent debate, and conclude with some prospects for future research.
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  • Precise Credences.Michael Titelbaum - 2019 - In Richard Pettigrew & Jonathan Weisberg (eds.), The Open Handbook of Formal Epistemology. PhilPaper Foundation. pp. 1-55.
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  • Full & Partial Belief.Konstantin Genin - 2019 - In Richard Pettigrew & Jonathan Weisberg (eds.), The Open Handbook of Formal Epistemology. PhilPapers Foundation. pp. 437-498.
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  • Bayesianism I: Introduction and Arguments in Favor.Kenny Easwaran - 2011 - Philosophy Compass 6 (5):312-320.
    Bayesianism is a collection of positions in several related fields, centered on the interpretation of probability as something like degree of belief, as contrasted with relative frequency, or objective chance. However, Bayesianism is far from a unified movement. Bayesians are divided about the nature of the probability functions they discuss; about the normative force of this probability function for ordinary and scientific reasoning and decision making; and about what relation (if any) holds between Bayesian and non-Bayesian concepts.
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  • Merging of Opinions and Probability Kinematics.Simon M. Huttegger - 2015 - Review of Symbolic Logic 8 (4):611-648.
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  • Updating, Supposing, and Maxent.Brian Skyrms - 1987 - Theory and Decision 22 (3):225-246.
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  • Modus Ponens and Modus Tollens for Conditional Probabilities, and Updating on Uncertain Evidence.Jordan Howard Sobel - 2009 - Theory and Decision 66 (2):103 - 148.
    There are narrowest bounds for P(h) when P(e) = y and P(h/e) = x, which bounds collapse to x as y goes to 1. A theorem for these bounds -- bounds for probable modus ponens -- entails a principle for updating on possibly uncertain evidence subject to these bounds that is a generalization of the principle for updating by conditioning on certain evidence. This way of updating on possibly uncertain evidence is appropriate when updating by ’probability kinematics’ or ’Jeffrey-conditioning’ is, (...)
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  • Foundations of Probability.Rachael Briggs - 2015 - Journal of Philosophical Logic 44 (6):625-640.
    The foundations of probability are viewed through the lens of the subjectivist interpretation. This article surveys conditional probability, arguments for probabilism, probability dynamics, and the evidential and subjective interpretations of probability.
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  • Self-Doubts and Dutch Strategies.Jordan Howard Sobel - 1987 - Australasian Journal of Philosophy 65 (1):56 – 81.
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