About this topic
Summary

In Bayesian epistemology, an updating principle is a principle that specifies or puts restrictions on the changes in an agent’s belief state that follow (or should follow) some initial change in the agent’s belief state (usually – but maybe not always – as a result of the agent being exposed to new evidence). Although in other academic fields a great deal of the discussion regarding updating principles touches upon their empirical fit to the way people actually update their beliefs, much of the relevant philosophical literature is normative. The central questions are whether, why and in which contexts, obeying different updating principles is rationally required. In the simplest (but not uncommon) case, where the agent’s belief state can be represented by a single probability distribution over a set of propositions, and the initial change is that of learning a new proposition (represented as raising the probability of the learnt proposition to 1), the most popular updating rule is Bayesian Conditionalization. Richard Jeffrey offered a generalization of Bayesian Conditionalization, usually called “Jeffrey’s conditionalization”, to cases in which, although there is some initial change in the agent’s belief state, the probability of no proposition in the set is raised to 1. Others have introduced, discussed and explored the formal features of other updating principles. These principles are usually ones that either cover cases to which Jeffrey’s conditionalization does not apply (such as cases of “growing awareness” in which the initial change is represented as an addition of new propositions to the set or cases in which the agent’s initial belief set cannot be represented by a single probability distribution over a set of propositions) or constitute generalizations of or alternatives to Bayesian Conditionalization and Jeffrey’s Conditionalization in specific contexts (such as Adams’ conditionalization for the case of learning conditional probabilities, Imaging which – in some contexts – seem to fit better with other intuitive epistemic principles or different types of pooling methods for the case of learning other agents’ beliefs).

Key works

Jeffrey 1992 introduces the idea of probability kinematics and discusses its features. Some important discussions of Jeffrey’s rule include Field 1978, Fraassen 1980 and Skyrms 1987. Bradley 2005 introduces and discusses Adams’ Conditionalization. In Bradley 2017 Bradley also discusses growing awareness and the relation between belief updating and the updating of desires and preferences. “Imaging” was introduced and discussed in Lewis 1976 and Gardenfors 1982. Leitgeb 2017 discusses the relation between Imaging and different belief aggregation methods. Some discussions of different problems associated with updating imprecise probabilities are White 2009, Bradley & Steele 2014 and Joyce 2010.

Introductions Jeffrey 2002
Related categories

363 found
Order:
1 — 50 / 363
  1. On Being a Random Sample.David Manley - manuscript
    It is well known that de se (or ‘self-locating’) propositions complicate the standard picture of how we should respond to evidence. This has given rise to a substantial literature centered around puzzles like Sleeping Beauty, Dr. Evil, and Doomsday—and it has also sparked controversy over a style of argument that has recently been adopted by theoretical cosmologists. These discussions often dwell on intuitions about a single kind of case, but it’s worth seeking a rule that can unify our treatment of (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   6 citations  
  2. Learning as Hypothesis Testing: Learning Conditional and Probabilistic Information.Jonathan Vandenburgh - manuscript
    Complex constraints like conditionals ('If A, then B') and probabilistic constraints ('The probability that A is p') pose problems for Bayesian theories of learning. Since these propositions do not express constraints on outcomes, agents cannot simply conditionalize on the new information. Furthermore, a natural extension of conditionalization, relative information minimization, leads to many counterintuitive predictions, evidenced by the sundowners problem and the Judy Benjamin problem. Building on the notion of a `paradigm shift' and empirical research in psychology and economics, I (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  3. Laying Sleeping Beauty to Rest.Masahiro Yamada - manuscript
    There are three main points of the paper. 1. There are straightforward ways of manipulating expected gains and losses that result in a divergence between fair betting odds and credence. Such manipulations are familiar from tools of finance. One can easily see that the Sleeping Beauty case is structured in such a way as to result in a divergence between fair betting odds and credence. 2. The inspection of credences and betting odds in certain betting situations shows that the two (...)
    Remove from this list   Direct download  
    Translate
     
     
    Export citation  
     
    Bookmark  
  4. My Way or Her Way: A Conundrum in Bayesian Epistemology of Disagreement.Tomoji Shogenji - manuscript
    The proportional weight view in epistemology of disagreement generalizes the equal weight view and proposes that we assign to judgments of different people weights that are proportional to their epistemic qualifications. It is shown that if the resulting degrees of confidence are to constitute a probability function, they must be the weighted arithmetic means of individual degrees of confidence, while if the resulting degrees of confidence are to obey the Bayesian rule of conditionalization, they must be the weighted geometric means (...)
    Remove from this list  
     
    Export citation  
     
    Bookmark   2 citations  
  5. An Accuracy‐Dominance Argument for Conditionalization.R. A. Briggs & Richard Pettigrew - forthcoming - Noûs.
  6. Updating for Externalists.J. Dmitri Gallow - forthcoming - Noûs.
    The externalist says that your evidence could fail to tell you what evidence you do or not do have. In that case, it could be rational for you to be uncertain about what your evidence is. This is a kind of uncertainty which orthodox Bayesian epistemology has difficulty modeling. For, if externalism is correct, then the orthodox Bayesian learning norms of conditionalization and reflection are inconsistent with each other. I recommend that an externalist Bayesian reject conditionalization. In its stead, I (...)
    Remove from this list   Direct download (5 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  7. Epistemic Modal Credence.Simon Goldstein - forthcoming - Philosophers' Imprint.
    Triviality results threaten plausible principles governing our credence in epistemic modal claims. This paper develops a new account of modal credence which avoids triviality. On the resulting theory, probabilities are assigned not to sets of worlds, but rather to sets of information state-world pairs. The theory avoids triviality by giving up the principle that rational credence is closed under conditionalization. A rational agent can become irrational by conditionalizing on new evidence. In place of conditionalization, the paper develops a new account (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  8. Probability for Epistemic Modalities.Simon Goldstein & Paolo Santorio - forthcoming - Philosophers' Imprint.
    This paper develops an information sensitive theory of the semantics and probability of conditionals and statements involving epistemic modals. The theory validates a number of principles linking probability and modality, including the principle that the probability of a conditional 'If A, then C' equals the probability of C, updated with A. The theory avoids so-called triviality results, which are standardly taken to show that principles of this sort cannot be validated. To achieve this, we deny that rational agents update their (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
  9. 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.
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  10. "Objective Purport, Relational Confirmation, and the Presumption of Moral Objectivism: A Probabilistic Argument From Moral Experience".Tanner Hammond - forthcoming - Southwest Philosophy Review.
    All else being equal, can granting the objective purport of moral experience support a presumption in favor of some form of moral objectivism? Don Loeb (2007) has argued that even if we grant that moral experience appears to present us with a realm of objective moral fact—something he denies we have reason to do in the first place—the objective purport of moral experience cannot by itself provide even prima facie support for moral objectivism. In this paper, I contend against Loeb (...)
    Remove from this list  
     
    Export citation  
     
    Bookmark  
  11. Kyburg.'The Rule of Adjunction and Reasonable Inference,'.E. Henry Jr - forthcoming - Journal of Philosophy.
    Remove from this list  
     
    Export citation  
     
    Bookmark  
  12. Generalized Conditionalization and the Sleeping Beauty Problem, II.Terence Horgan - forthcoming - Erkenntnis.
    In “Generalized Conditionalization and the Sleeping Beauty Problem,” Anna Mahtani and I offer a new argument for thirdism that relies on what we call “generalized conditionalization.” Generalized conditionalization goes beyond conventional conditionalization in two respects: first, by sometimes deploying a space of synchronic, essentially temporal, candidate-possibilities that are not “prior” possibilities; and second, by allowing for the use of preliminary probabilities that arise by first bracketing, and then conditionalizing upon, “old evidence.” In “Beauty and Conditionalization: Reply to Horgan and Mahtani,” (...)
    Remove from this list   Direct download  
    Translate
     
     
    Export citation  
     
    Bookmark   3 citations  
  13. The Art of Learning.Jason Konek - forthcoming - Oxford Studies in Epistemology 7.
    Confirmational holism is at odds with Jeffrey conditioning --- the orthodox Bayesian policy for accommodating uncertain learning experiences. Two of the great insights of holist epistemology are that the effects of experience ought to be mediated by one's background beliefs, and the support provided by one's learning experience can and often is undercut by subsequent learning. Jeffrey conditioning fails to vindicate either of these insights. My aim is to describe and defend a new updating policy that does better. In addition (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  14. Not So Phenomenal!Maria Lasonen-Aarnio & John Hawthorne - forthcoming - The Philosophical Review.
    Our main aims in this paper is to discuss and criticise the core thesis of a position that has become known as phenomenal conservatism. According to this thesis, its seeming to one that p provides enough justification for a belief in p to be prima facie justified (a thesis we label Standard Phenomenal Conservatism). This thesis captures the special kind of epistemic import that seemings are claimed to have. To get clearer on this thesis, we embed it, first, in a (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  15. Kolmogorov Conditionalizers Can Be Dutch Booked.Alexander Meehan & Snow Zhang - forthcoming - Review of Symbolic Logic:1-36.
    A vexing question in Bayesian epistemology is how an agent should update on evidence which she assigned zero prior credence. Some theorists have suggested that, in such cases, the agent should update by Kolmogorov conditionalization, a norm based on Kolmogorov’s theory of regular conditional distributions. However, it turns out that in some situations, a Kolmogorov conditionalizer will plan to always assign a posterior credence of zero to the evidence she learns. Intuitively, such a plan is irrational and easily Dutch bookable. (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  16. Accuracy-Dominance and Conditionalization.Michael Nielsen - forthcoming - Philosophical Studies:1-20.
    Epistemic decision theory produces arguments with both normative and mathematical premises. I begin by arguing that philosophers should care about whether the mathematical premises (1) are true, (2) are strong, and (3) admit simple proofs. I then discuss a theorem that Briggs and Pettigrew (2020) use as a premise in a novel accuracy-dominance argument for conditionalization. I argue that the theorem and its proof can be improved in a number of ways. First, I present a counterexample that shows that one (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark  
  17. A New Argument for Kolomogorov Conditionalization.Michael Nielsen - forthcoming - Review of Symbolic Logic:1-16.
    This paper contributes to a recent research program that extends arguments supporting elementary conditionalization to arguments supporting conditionalization with general, measure-theoretic conditional probabilities. I begin by suggesting an amendment to the framework that Rescorla has used to characterize regular conditional probabilities in terms of avoiding Dutch book. If we wish to model learning scenarios in which an agent gains complete membership knowledge about some subcollection of the events of interest to her, then we should focus on updating policies that are (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  18. Coherence & Confirmation: The Epistemic Limitations to the Impossibility Theorems.Ted Poston - forthcoming - Kriterion - Journal of Philosophy.
    It is a widespread intuition that the coherence of independent reports provides a powerful reason to believe that the reports are true. Formal results by Huemer (1997), Olsson (2002, 2005), and Bovens and Hartmann (2003) prove that, under certain conditions, coherence cannot increase the probability of the target claim. These formal results, known as ‘the impossibility theorems’ have been widely discussed in the literature. They are taken to have significant epistemic upshot. In particular, they are taken to show that reports (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  19. Sleeping Beauty's Evidence.Jeffrey Sanford Russell - forthcoming - In Maria Lasonen-Aarnio & Clayton M. Littlejohn (eds.), The Routledge Handbook of the Philosophy of Evidence. Routledge.
    What degrees of belief does Sleeping Beauty's evidence support? That depends.
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark  
  20. Temporally Continuous Probability Kinematics.Kevin Blackwell - 2021 - Dissertation, University of Michigan
    The heart of my dissertation project is the proposal of a new updating rule for responding to learning experiences consisting of continuous streams of evidence. I suggest characterizing this kind of learning experience as a continuous stream of stipulated credal derivatives, and show that Continuous Probability Kinematics is the uniquely coherent response to such a stream which satisfies a continuous analogue of Rigidity – the core property of both Bayesian and Jeffrey conditionalization. In the first chapter, I define neighborhood norms (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  21. Not So Phenomenal!John Hawthorne & Maria Lasonen-Aarnio - 2021 - Philosophical Review 130 (1):1-43.
    The main aims in this article are to discuss and criticize the core thesis of a position that has become known as phenomenal conservatism. According to this thesis, its seeming to one that p provides enough justification for a belief in p to be prima facie justified. This thesis captures the special kind of epistemic import that seemings are claimed to have. To get clearer on this thesis, the article embeds it, first, in a probabilistic framework in which updating on (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  22. A note on deterministic updating and van Fraassen’s symmetry argument for conditionalization.Richard Pettigrew - 2021 - Philosophical Studies 178 (2):665-673.
    In a recent paper, Pettigrew argues that the pragmatic and epistemic arguments for Bayesian updating are based on an unwarranted assumption, which he calls deterministic updating, and which says that your updating plan should be deterministic. In that paper, Pettigrew did not consider whether the symmetry arguments due to Hughes and van Fraassen make the same assumption Scientific inquiry in philosophical perspective. University Press of America, Lanham, pp. 183–223, 1987). In this note, I show that they do.
    Remove from this list   Direct download (4 more)  
    Translate
     
     
    Export citation  
     
    Bookmark  
  23. Self-Locating Belief and Updating on Learning.Darren Bradley - 2020 - Mind 129 (514):579-584.
    Self-locating beliefs cause a problem for conditionalization. Miriam Schoenfield offers a solution: that on learning E, agents should update on the fact that they learned E. However, Schoenfield is not explicit about whether the fact that they learned E is self-locating. I will argue that if the fact that they learned E is self-locating then the original problem has not been addressed, and if the fact that they learned E is not self-locating then the theory generates implausible verdicts which Schoenfield (...)
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    Bookmark  
  24. Time-Slice Rationality and Self-Locating Belief.David Builes - 2020 - Philosophical Studies 177 (10):3033-3049.
    The epistemology of self-locating belief concerns itself with how rational agents ought to respond to certain kinds of indexical information. I argue that those who endorse the thesis of Time-Slice Rationality ought to endorse a particular view about the epistemology of self-locating belief, according to which ‘essentially indexical’ information is never evidentially relevant to non-indexical matters. I close by offering some independent motivations for endorsing Time-Slice Rationality in the context of the epistemology of self-locating belief.
    Remove from this list   Direct download (3 more)  
    Translate
     
     
    Export citation  
     
    Bookmark   1 citation  
  25. Accurate Updating for the Risk Sensitive.Catrin Campbell-Moore & Bernhard Salow - 2020 - British Journal for the Philosophy of Science:axaa006.
    Philosophers have recently attempted to justify particular belief revision procedures by arguing that they are the optimal means towards the epistemic end of accurate credences. These attempts, however, presuppose that means should be evaluated according to classical expected utility theory; and there is a long tradition maintaining that expected utility theory is too restrictive as a theory of means–end rationality, ruling out too many natural ways of taking risk into account. In this paper, we investigate what belief-revision procedures are supported (...)
    Remove from this list   Direct download (7 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  26. Commutativity, Normativity, and Holism: Lange Revisited.Lisa Cassell - 2020 - Canadian Journal of Philosophy 50 (2):159-173.
    Lange (2000) famously argues that although Jeffrey Conditionalization is non-commutative over evidence, it’s not defective in virtue of this feature. Since reversing the order of the evidence in a sequence of updates that don’t commute does not reverse the order of the experiences that underwrite these revisions, the conditions required to generate commutativity failure at the level of experience will fail to hold in cases where we get commutativity failure at the level of evidence. If our interest in commutativity is, (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  27. Learning From Conditionals.Benjamin Eva, Stephan Hartmann & Soroush Rafiee Rad - 2020 - Mind 129 (514):461-508.
    In this article, we address a major outstanding question of probabilistic Bayesian epistemology: how should a rational Bayesian agent update their beliefs upon learning an indicative conditional? A number of authors have recently contended that this question is fundamentally underdetermined by Bayesian norms, and hence that there is no single update procedure that rational agents are obliged to follow upon learning an indicative conditional. Here we resist this trend and argue that a core set of widely accepted Bayesian norms is (...)
    Remove from this list   Direct download (6 more)  
     
    Export citation  
     
    Bookmark   3 citations  
  28. Confirmation Based on Analogical Inference: Bayes Meets Jeffrey.Christian J. Feldbacher-Escamilla & Alexander Gebharter - 2020 - Canadian Journal of Philosophy 50 (2):174-194.
    Certain hypotheses cannot be directly confirmed for theoretical, practical, or moral reasons. For some of these hypotheses, however, there might be a workaround: confirmation based on analogical reasoning. In this paper we take up Dardashti, Hartmann, Thébault, and Winsberg’s (in press) idea of analyzing confirmation based on analogical inference Baysian style. We identify three types of confirmation by analogy and show that Dardashti et al.’s approach can cover two of them. We then highlight possible problems with their model as a (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark   3 citations  
  29. Anchoring in Deliberations.Stephan Hartmann & Soroush Rafiee Rad - 2020 - Erkenntnis 85:1041-1069.
    Deliberation is a standard procedure to make decisions in not too large groups. It has the advantage that the group members can learn from each other and that, at the end, often a consensus emerges that everybody endorses. But a deliberation procedure also has a number of disadvantages. E.g., what consensus is reached usually depends on the order in which the different group members speak. More specifically, the group member who speaks first often has an unproportionally high impact on the (...)
    Remove from this list   Direct download (11 more)  
     
    Export citation  
     
    Bookmark  
  30. Regression to the Mean and Judy Benjamin.Randall G. McCutcheon - 2020 - Synthese 197 (3):1343-1355.
    Van Fraassen's Judy Benjamin problem asks how one ought to update one's credence in A upon receiving evidence of the sort ``A may or may not obtain, but B is k times likelier than C'', where {A,B,C} is a partition. Van Fraassen's solution, in the limiting case of increasing k, recommends a posterior converging to the probability of A conditional on A union B, where P is one's prior probability function. Grove and Halpern, and more recently Douven and Romeijn, have (...)
    Remove from this list   Direct download (6 more)  
     
    Export citation  
     
    Bookmark  
  31. Jeffrey Meets Kolmogorov: A General Theory of Conditioning.Alexander Meehan & Snow Zhang - 2020 - Journal of Philosophical Logic 49 (5):941-979.
    Jeffrey conditionalization is a rule for updating degrees of belief in light of uncertain evidence. It is usually assumed that the partitions involved in Jeffrey conditionalization are finite and only contain positive-credence elements. But there are interesting examples, involving continuous quantities, in which this is not the case. Q1 Can Jeffrey conditionalization be generalized to accommodate continuous cases? Meanwhile, several authors, such as Kenny Easwaran and Michael Rescorla, have been interested in Kolmogorov’s theory of regular conditional distributions as a possible (...)
    Remove from this list   Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark   2 citations  
  32. Holistic Conditionalization and Underminable Perceptual Learning.Brian T. Miller - 2020 - Philosophy and Phenomenological Research 101 (1):130-149.
    Seeing a red hat can (i) increase my credence in the hat is red, and (ii) introduce a negative dependence between that proposition and po- tential undermining defeaters such as the light is red. The rigidity of Jeffrey Conditionalization makes this awkward, as rigidity preserves inde- pendence. The picture is less awkward given ‘Holistic Conditionalization’, or so it is claimed. I defend Jeffrey Conditionalization’s consistency with underminable perceptual learning and its superiority to Holistic Conditionalization, arguing that the latter is merely (...)
    Remove from this list   Direct download (8 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  33. A Puzzle About Experts, Evidential Screening-Off and Conditionalization.Ittay Nissan-Rozen - 2020 - Episteme 17 (1):64-72.
    I present a puzzle about the epistemic role beliefs about experts' beliefs play in a rational agent's system of beliefs. It is shown that accepting the claim that an expert's degree of belief in a proposition, A, screens off the evidential support another proposition, B, gives to A in case the expert knows and is certain about whether B is true, leads in some cases to highly unintuitive conclusions. I suggest a solution to the puzzle according to which evidential screening (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  34. What is conditionalization, and why should we do it?Richard Pettigrew - 2020 - Philosophical Studies 177 (11):3427-3463.
    Conditionalization is one of the central norms of Bayesian epistemology. But there are a number of competing formulations, and a number of arguments that purport to establish it. In this paper, I explore which formulations of the norm are supported by which arguments. In their standard formulations, each of the arguments I consider here depends on the same assumption, which I call Deterministic Updating. I will investigate whether it is possible to amend these arguments so that they no longer depend (...)
    Remove from this list   Direct download (4 more)  
    Translate
     
     
    Export citation  
     
    Bookmark   3 citations  
  35. Open-Minded Orthodox Bayesianism by Epsilon-Conditionalization.Eric Raidl - 2020 - British Journal for the Philosophy of Science 71 (1):139-176.
    Orthodox Bayesianism endorses revising by conditionalization. This paper investigates the zero-raising problem, or equivalently the certainty-dropping problem of orthodox Bayesianism: previously neglected possibilities remain neglected, although the new evidence might suggest otherwise. Yet, one may want to model open-minded agents, that is, agents capable of raising previously neglected possibilities. Different reasons can be given for open-mindedness, one of which is fallibilism. The paper proposes a family of open-minded propositional revisions depending on a parameter ϵ. The basic idea is this: first (...)
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  36. An Accuracy Argument in Favor of Ranking Theory.Eric Raidl & Wolfgang Spohn - 2020 - Journal of Philosophical Logic 49 (2):283-313.
    Fitelson and McCarthy have proposed an accuracy measure for confidence orders which favors probability measures and Dempster-Shafer belief functions as accounts of degrees of belief and excludes ranking functions. Their accuracy measure only penalizes mistakes in confidence comparisons. We propose an alternative accuracy measure that also rewards correct confidence comparisons. Thus we conform to both of William James’ maxims: “Believe truth! Shun error!” We combine the two maxims, penalties and rewards, into one criterion that we call prioritized accuracy optimization. That (...)
    Remove from this list   Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark  
  37. Expert Deference as a Belief Revision Schema.Joe Roussos - 2020 - Synthese:1-28.
    When an agent learns of an expert's credence in a proposition about which they are an expert, the agent should defer to the expert and adopt that credence as their own. This is a popular thought about how agents ought to respond to (ideal) experts. In a Bayesian framework, it is often modelled by endowing the agent with a set of priors that achieves this result. But this model faces a number of challenges, especially when applied to non-ideal agents (who (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark  
  38. Policymaking Under Scientific Uncertainty.Joe Roussos - 2020 - Dissertation, London School of Economics
    Policymakers who seek to make scientifically informed decisions are constantly confronted by scientific uncertainty and expert disagreement. This thesis asks: how can policymakers rationally respond to expert disagreement and scientific uncertainty? This is a work of non-ideal theory, which applies formal philosophical tools developed by ideal theorists to more realistic cases of policymaking under scientific uncertainty. I start with Bayesian approaches to expert testimony and the problem of expert disagreement, arguing that two popular approaches— supra-Bayesianism and the standard model of (...)
    Remove from this list   Direct download  
     
    Export citation  
     
    Bookmark   1 citation  
  39. Conditional Degree of Belief and Bayesian Inference.Jan Sprenger - 2020 - Philosophy of Science 87 (2):319-335.
    Why are conditional degrees of belief in an observation E, given a statistical hypothesis H, aligned with the objective probabilities expressed by H? After showing that standard replies are not satisfactory, I develop a suppositional analysis of conditional degree of belief, transferring Ramsey’s classical proposal to statistical inference. The analysis saves the alignment, explains the role of chance-credence coordination, and rebuts the charge of arbitrary assessment of evidence in Bayesian inference. Finally, I explore the implications of this analysis for Bayesian (...)
    Remove from this list   Direct download (3 more)  
     
    Export citation  
     
    Bookmark   5 citations  
  40. 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 (...)
    Remove from this list   Direct download (3 more)  
    Translate
     
     
    Export citation  
     
    Bookmark  
  41. Credence for conclusions: a brief for Jeffrey’s rule.John R. Welch - 2020 - Synthese 197 (5):2051-2072.
    Some arguments are good; others are not. How can we tell the difference? This article advances three proposals as a partial answer to this question. The proposals are keyed to arguments conditioned by different degrees of uncertainty: mild, where the argument’s premises are hedged with point-valued probabilities; moderate, where the premises are hedged with interval probabilities; and severe, where the premises are hedged with non-numeric plausibilities such as ‘very likely’ or ‘unconfirmed’. For mild uncertainty, the article proposes to apply a (...)
    Remove from this list   Direct download (2 more)  
    Translate
     
     
    Export citation  
     
    Bookmark  
  42. A Theory of Epistemic Risk.Boris Babic - 2019 - Philosophy of Science 86 (3):522-550.
    I propose a general alethic theory of epistemic risk according to which the riskiness of an agent’s credence function encodes her relative sensitivity to different types of graded error. After motivating and mathematically developing this approach, I show that the epistemic risk function is a scaled reflection of expected inaccuracy. This duality between risk and information enables us to explore the relationship between attitudes to epistemic risk, the choice of scoring rules in epistemic utility theory, and the selection of priors (...)
    Remove from this list   Direct download (8 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  43. Self‐Locating Evidence and the Metaphysics of Time.David Builes - 2019 - Philosophy and Phenomenological Research 99 (2):478-490.
    I argue that different views in the metaphysics of time make different observational predictions in both classical and relativistic cases. Because different views in the metaphysics of time differ over which facts are merely indexical facts, they make different observational predictions about certain self-locating propositions. I argue for this thesis by distinguishing the three main updating procedures that apply in cases of self-locating uncertainty, and I present a series of cases which cumulatively show that every one of these updating procedures (...)
    Remove from this list   Direct download (5 more)  
     
    Export citation  
     
    Bookmark   2 citations  
  44. Probability, Coherent Belief and Coherent Belief Changes.John Cantwell & Hans Rott - 2019 - Annals of Mathematics and Artificial Intelligence 87 (3):259-291.
    This paper is about the statics and dynamics of belief states that are represented by pairs consisting of an agent's credences (represented by a subjective probability measure) and her categorical beliefs (represented by a set of possible worlds). Regarding the static side, we argue that the latter proposition should be coherent with respect to the probability measure and that its probability should reach a certain threshold value. On the dynamic side, we advocate Jeffrey conditionalisation as the principal mode of changing (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  45. Higher-Order Beliefs and the Undermining Problem for Bayesianism.Lisa Cassell - 2019 - Acta Analytica 34 (2):197-213.
    Jonathan Weisberg has argued that Bayesianism’s rigid updating rules make Bayesian updating incompatible with undermining defeat. In this paper, I argue that when we attend to the higher-order beliefs we must ascribe to agents in the kinds of cases Weisberg considers, the problem he raises disappears. Once we acknowledge the importance of higher-order beliefs to the undermining story, we are led to a different understanding of how these cases arise. And on this different understanding of things, the rigid nature of (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  46. Accuracy and Ur-Prior Conditionalization.Nilanjan Das - 2019 - Review of Symbolic Logic 12 (1):62-96.
    Recently, several epistemologists have defended an attractive principle of epistemic rationality, which we shall call Ur-Prior Conditionalization. In this essay, I ask whether we can justify this principle by appealing to the epistemic goal of accuracy. I argue that any such accuracy-based argument will be in tension with Evidence Externalism, i.e., the view that agent's evidence may entail non-trivial propositions about the external world. This is because any such argument will crucially require the assumption that, independently of all empirical evidence, (...)
    Remove from this list   Direct download (2 more)  
     
    Export citation  
     
    Bookmark   3 citations  
  47. 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 (...)
    Remove from this list   Direct download (8 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  48. The Modal Logic of Bayesian Belief Revision.Zalán Gyenis, Miklós Rédei & William Brown - 2019 - Journal of Philosophical Logic 48 (5):809-824.
    In Bayesian belief revision a Bayesian agent revises his prior belief by conditionalizing the prior on some evidence using Bayes’ rule. We define a hierarchy of modal logics that capture the logical features of Bayesian belief revision. Elements in the hierarchy are distinguished by the cardinality of the set of elementary propositions on which the agent’s prior is defined. Inclusions among the modal logics in the hierarchy are determined. By linking the modal logics in the hierarchy to the strongest modal (...)
    Remove from this list   Direct download (6 more)  
     
    Export citation  
     
    Bookmark   4 citations  
  49. A Pragmatic Argument Against Equal Weighting.Ittay Nissan-Rozen & Levi Spectre - 2019 - Synthese 196 (10):4211-4227.
    We present a minimal pragmatic restriction on the interpretation of the weights in the “Equal Weight View” regarding peer disagreement and show that the view cannot respect it. Based on this result we argue against the view. The restriction is the following one: if an agent, $$\hbox {i}$$ i, assigns an equal or higher weight to another agent, $$\hbox {j}$$ j,, he must be willing—in exchange for a positive and certain payment—to accept an offer to let a completely rational and (...)
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    Bookmark   1 citation  
  50. Two Approaches to Belief Revision.Ted Shear & Branden Fitelson - 2019 - Erkenntnis 84 (3):487-518.
    In this paper, we compare and contrast two methods for the revision of qualitative beliefs. The first method is generated by a simplistic diachronic Lockean thesis requiring coherence with the agent’s posterior credences after conditionalization. The second method is the orthodox AGM approach to belief revision. Our primary aim is to determine when the two methods may disagree in their recommendations and when they must agree. We establish a number of novel results about their relative behavior. Our most notable finding (...)
    Remove from this list   Direct download (4 more)  
     
    Export citation  
     
    Bookmark   13 citations  
1 — 50 / 363