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Bayesian Epistemology

In Sven Bernecker & Duncan Pritchard (eds.), The Routledge Companion to Epistemology. New York: Routledge. pp. 609-620 (2010)

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  1. Confirmation and Reduction: a Bayesian Account.Foad Dizadji-Bahmani, Roman Frigg & Stephan Hartmann - 2010 - Synthese 179 (2):321-338.
    Various scientific theories stand in a reductive relation to each other. In a recent article, we have argued that a generalized version of the Nagel-Schaffner model (GNS) is the right account of this relation. In this article, we present a Bayesian analysis of how GNS impacts on confirmation. We formalize the relation between the reducing and the reduced theory before and after the reduction using Bayesian networks, and thereby show that, post-reduction, the two theories are confirmatory of each other. We (...)
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  • Individual Belief Revision Dynamics in a Group Context.Igor Volzhanin, Ulrike Hahn, Martin Jönsson & Erik J. Olsson - unknown
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  • The probabilistic no miracles argument.Jan Sprenger - 2016 - European Journal for Philosophy of Science 6 (2):173-189.
    This paper develops a probabilistic reconstruction of the No Miracles Argument in the debate between scientific realists and anti-realists. The goal of the paper is to clarify and to sharpen the NMA by means of a probabilistic formalization. In particular, we demonstrate that the persuasive force of the NMA depends on the particular disciplinary context where it is applied, and the stability of theories in that discipline. Assessments and critiques of "the" NMA, without reference to a particular context, are misleading (...)
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  • Structuring reality.Naomi Margaret Claire Thompson - 2014 - Dissertation, University of Birmingham
    This thesis explores attempts to characterise the structure of reality. Three notions stand out: Lewisian naturalness, Sider’s ‘structure’, and grounding, where the latter has become the most popular way to characterise the structure of reality in the contemporary literature. I argue that none of these notions, as they are currently understood, are suited for limning the metaphysical structure of reality. In the first part of the thesis I argue that, by the lights of the relevant theories, both naturalness and structure (...)
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  • Toward a Grammar of Bayesian Confirmation.Vincenzo Crupi, Roberto Festa & Carlo Buttasi - 2009 - In M. Suàrez, M. Dorato & M. Rèdei (eds.), EPSA Epistemology and Methodology of Science: Launch of the European Philosophy of Science Association. Springer. pp. 73--93.
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  • (1 other version)Formal Epistemology.Gregory Wheeler - 2010 - In Andrew Cullison (ed.), A Companion to Epistemology. New York: Continuum Press.
    Yet, in broader terms, formal epistemology is not merely a methodological tool for epistemologists, but a discipline in its own right. On this programmatic view, formal epistemology is an interdisciplinary research program that covers work by philosophers, mathematicians, computer scientists, statisticians, psychologists, operations researchers, and economists who aim to give mathematical and sometimes computational representations of, along with sound strategies for reasoning about, knowledge, belief, judgment and decision making.
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  • Probability, confirmation, and the conjunction fallacy.Crupi Vincenzo, Fitelson Branden & Tentori Katya - 2008 - Thinking and Reasoning 14 (2):182-199.
    The conjunction fallacy has been a key topic in debates on the rationality of human reasoning and its limitations. Despite extensive inquiry, however, the attempt of providing a satisfactory account of the phenomenon has proven challenging. Here, we elaborate the suggestion (first discussed by Sides et al., 2001) that in standard conjunction problems the fallacious probability judgments experimentally observed are typically guided by sound assessments of confirmation relations, meant in terms of contemporary Bayesian confirmation theory. Our main formal result is (...)
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  • Why bounded rationality (in epistemology)?David Thorstad - 2024 - Philosophy and Phenomenological Research 108 (2):396-413.
    Bounded rationality gets a bad rap in epistemology. It is argued that theories of bounded rationality are overly context‐sensitive; conventionalist; or dependent on ordinary language (Carr, 2022; Pasnau, 2013). In this paper, I have three aims. The first is to set out and motivate an approach to bounded rationality in epistemology inspired by traditional theories of bounded rationality in cognitive science. My second aim is to show how this approach can answer recent challenges raised for theories of bounded rationality. My (...)
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  • A Causal Safety Criterion for Knowledge.Jonathan Vandenburgh - 2024 - Erkenntnis 89 (8):3287-3307.
    Safety purports to explain why cases of accidentally true belief are not knowledge, addressing Gettier cases and cases of belief based on statistical evidence. However, problems arise for using safety as a condition on knowledge: safety is not necessary for knowledge and cannot always explain the Gettier cases and cases of statistical evidence it is meant to address. In this paper, I argue for a new modal condition designed to capture the non-accidental relationship between facts and evidence required for knowledge: (...)
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  • Epistemic Probabilities are Degrees of Support, not Degrees of (Rational) Belief.Nevin Climenhaga - 2024 - Philosophy and Phenomenological Research 108 (1):153-176.
    I argue that when we use ‘probability’ language in epistemic contexts—e.g., when we ask how probable some hypothesis is, given the evidence available to us—we are talking about degrees of support, rather than degrees of belief. The epistemic probability of A given B is the mind-independent degree to which B supports A, not the degree to which someone with B as their evidence believes A, or the degree to which someone would or should believe A if they had B as (...)
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  • Freedom and chance.Mark Wulff Carstensen - unknown
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  • Bayes Nets and Rationality.Stephan Hartmann - 2021 - In Markus Knauff & Wolfgang Spohn (eds.), The Handbook of Rationality. London: MIT Press.
    Bayes nets are a powerful tool for researchers in statistics and artificial intelligence. This chapter demonstrates that they are also of much use for philosophers and psychologists interested in (Bayesian) rationality. To do so, we outline the general methodology of Bayes nets modeling in rationality research and illustrate it with several examples from the philosophy and psychology of reasoning and argumentation. Along the way, we discuss the normative foundations of Bayes nets modeling and address some of the methodological problems it (...)
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  • Triviality Results, Conditional Probability, and Restrictor Conditionals.Jonathan Vandenburgh - manuscript
    Conditional probability is often used to represent the probability of the conditional. However, triviality results suggest that the thesis that the probability of the conditional always equals conditional probability leads to untenable conclusions. In this paper, I offer an interpretation of this thesis in a possible worlds framework, arguing that the triviality results make assumptions at odds with the use of conditional probability. I argue that these assumptions come from a theory called the operator theory and that the rival restrictor (...)
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  • Assessing Scientific Theories: The Bayesian Approach.Stephan Hartmann & Radin Dardashti - 2019 - In Dawid Richard, Dardashti Radin & Thebault Karim (eds.), Epistemology of Fundamental Physics: Why Trust a Theory? Cambridge University Press. pp. 67–83.
    Scientific theories are used for a variety of purposes. For example, physical theories such as classical mechanics and electrodynamics have important applications in engineering and technology, and we trust that this results in useful machines, stable bridges, and the like. Similarly, theories such as quantum mechanics and relativity theory have many applications as well. Beyond that, these theories provide us with an understanding of the world and address fundamental questions about space, time, and matter. Here we trust that the answers (...)
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  • Holistic Conditionalization and Underminable Perceptual Learning.Brian T. Miller - 2019 - 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 (...)
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  • Cross-Cultural Differences in Informal Argumentation: Norms, Inductive Biases and Evidentiality.Hatice Karaslaan, Annette Hohenberger, Hilmi Demir, Simon Hall & Mike Oaksford - 2018 - Journal of Cognition and Culture 18 (3-4):358-389.
    Cross-cultural differences in argumentation may be explained by the use of different norms of reasoning. However, some norms derive from, presumably universal, mathematical laws. This inconsistency can be resolved, by considering that some norms of argumentation, like Bayes theorem, are mathematical functions. Systematic variation in the inputs may produce culture-dependent inductive biases although the function remains invariant. This hypothesis was tested by fitting a Bayesian model to data on informal argumentation from Turkish and English cultures, which linguistically mark evidence quality (...)
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  • General properties of bayesian learning as statistical inference determined by conditional expectations.Zalán Gyenis & Miklós Rédei - 2017 - Review of Symbolic Logic 10 (4):719-755.
    We investigate the general properties of general Bayesian learning, where “general Bayesian learning” means inferring a state from another that is regarded as evidence, and where the inference is conditionalizing the evidence using the conditional expectation determined by a reference probability measure representing the background subjective degrees of belief of a Bayesian Agent performing the inference. States are linear functionals that encode probability measures by assigning expectation values to random variables via integrating them with respect to the probability measure. If (...)
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  • Hawking radiation and analogue experiments: A Bayesian analysis.Radin Dardashti, Stephan Hartmann, Karim P. Y. Thébault & Eric Winsberg - 2019 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 67:1-11.
    We present a Bayesian analysis of the epistemology of analogue experiments with particular reference to Hawking radiation. Provided such experiments can be externally validated via universality arguments, we prove that they are confirmatory in Bayesian terms. We then provide a formal model for the scaling behaviour of the confirmation measure for multiple distinct realisations of the analogue system and isolate a generic saturation feature. Finally, we demonstrate that different potential analogue realisations could provide different levels of confirmation. Our results thus (...)
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  • Popper's severity of test as an intuitive probabilistic model of hypothesis testing.Fenna H. Poletiek - 2009 - Behavioral and Brain Sciences 32 (1):99-100.
    Severity of Test (SoT) is an alternative to Popper's logical falsification that solves a number of problems of the logical view. It was presented by Popper himself in 1963. SoT is a less sophisticated probabilistic model of hypothesis testing than Oaksford & Chater's (O&C's) information gain model, but it has a number of striking similarities. Moreover, it captures the intuition of everyday hypothesis testing.
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  • Conditional Learning Through Causal Models.Jonathan Vandenburgh - 2020 - Synthese (1-2):2415-2437.
    Conditional learning, where agents learn a conditional sentence ‘If A, then B,’ is difficult to incorporate into existing Bayesian models of learning. This is because conditional learning is not uniform: in some cases, learning a conditional requires decreasing the probability of the antecedent, while in other cases, the antecedent probability stays constant or increases. I argue that how one learns a conditional depends on the causal structure relating the antecedent and the consequent, leading to a causal model of conditional learning. (...)
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  • Having a look at the Bayes Blind Spot.Miklós Rédei & Zalán Gyenis - 2019 - Synthese 198 (4):3801-3832.
    The Bayes Blind Spot of a Bayesian Agent is, by definition, the set of probability measures on a Boolean σ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sigma $$\end{document}-algebra that are absolutely continuous with respect to the background probability measure of a Bayesian Agent on the algebra and which the Bayesian Agent cannot learn by a single conditionalization no matter what evidence he has about the elements in the Boolean σ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sigma (...)
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  • On the Modal Logic of Jeffrey Conditionalization.Zalán Gyenis - 2018 - Logica Universalis 12 (3-4):351-374.
    We continue the investigations initiated in the recent papers where Bayes logics have been introduced to study the general laws of Bayesian belief revision. In Bayesian belief revision a Bayesian agent revises his prior belief by conditionalizing the prior on some evidence using the Bayes rule. In this paper we take the more general Jeffrey formula as a conditioning device and study the corresponding modal logics that we call Jeffrey logics, focusing mainly on the countable case. The containment relations among (...)
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  • A Novel Solution to the Problem of Old Evidence.Jan Sprenger - 2015 - Philosophy of Science 82 (3):383-401.
    One of the most troubling and persistent challenges for Bayesian Confirmation Theory is the Problem of Old Evidence. The problem arises for anyone who models scientific reasoning by means of Bayesian Conditionalization. This article addresses the problem as follows: First, I clarify the nature and varieties of the POE and analyze various solution proposals in the literature. Second, I present a novel solution that combines previous attempts while making weaker and more plausible assumptions. Third and last, I summarize my findings (...)
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  • The No Alternatives Argument.Richard Dawid, Stephan Hartmann & Jan Sprenger - 2015 - British Journal for the Philosophy of Science 66 (1):213-234.
    Scientific theories are hard to find, and once scientists have found a theory, H, they often believe that there are not many distinct alternatives to H. But is this belief justified? What should scientists believe about the number of alternatives to H, and how should they change these beliefs in the light of new evidence? These are some of the questions that we will address in this article. We also ask under which conditions failure to find an alternative to H (...)
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  • Intertheoretic Reduction, Confirmation, and Montague’s Syntax-Semantics Relation.Kristina Liefke & Stephan Hartmann - 2018 - Journal of Logic, Language and Information 27 (4):313-341.
    Intertheoretic relations are an important topic in the philosophy of science. However, since their classical discussion by Ernest Nagel, such relations have mostly been restricted to relations between pairs of theories in the natural sciences. This paper presents a case study of a new type of intertheoretic relation that is inspired by Montague’s analysis of the linguistic syntax-semantics relation. The paper develops a simple model of this relation. To motivate the adoption of our new model, we show that this model (...)
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  • Significance testing, p-values and the principle of total evidence.Bengt Autzen - 2016 - European Journal for Philosophy of Science 6 (2):281-295.
    The paper examines the claim that significance testing violates the Principle of Total Evidence. I argue that p-values violate PTE for two-sided tests but satisfy PTE for one-sided tests invoking a sufficient test statistic independent of the preferred theory of evidence. While the focus of the paper is to evaluate a particular claim about the relationship of significance testing and PTE, I clarify the reading of this methodological principle along the way.
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  • How the conjunction fallacy is tied to probabilistic confirmation: Some remarks on Schupbach (2009).Katya Tentori & Vincenzo Crupi - 2012 - Synthese 184 (1):3-12.
    Crupi et al. (Think Reason 14:182–199, 2008) have recently advocated and partially worked out an account of the conjunction fallacy phenomenon based on the Bayesian notion of confirmation. In response, Schupbach (2009) presented a critical discussion as following from some novel experimental results. After providing a brief restatement and clarification of the meaning and scope of our original proposal, we will outline Schupbach’s results and discuss his interpretation thereof arguing that they do not actually undermine our point of view if (...)
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  • The uncertain reasoner: Bayes, logic, and rationality.Mike Oaksford & Nick Chater - 2009 - Behavioral and Brain Sciences 32 (1):105-120.
    Human cognition requires coping with a complex and uncertain world. This suggests that dealing with uncertainty may be the central challenge for human reasoning. In Bayesian Rationality we argue that probability theory, the calculus of uncertainty, is the right framework in which to understand everyday reasoning. We also argue that probability theory explains behavior, even on experimental tasks that have been designed to probe people's logical reasoning abilities. Most commentators agree on the centrality of uncertainty; some suggest that there is (...)
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  • Confirmation by Explanation: A Bayesian Justification of IBE.Marko Tesic, Benjamin Eva & Stephan Hartmann - manuscript
    We provide a novel Bayesian justification of inference to the best explanation. More specifically, we present conditions under which explanatory considerations can provide a significant confirmatory boost for hypotheses that provide the best explanation of the relevant evidence. Furthermore, we show that the proposed Bayesian model of IBE is able to deal naturally with the best known criticisms of IBE such as van Fraassen?s?bad lot? argument.
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  • Causal reasoning in economics: a selective exploration of semantic, epistemic and dynamical aspects.François Claveau - 2013 - Erasmus Journal for Philosophy and Economics 6 (2):122.
    Economists reason causally. Like many other scientists, they aim at formulating justified causal claims about their object of study. This thesis contributes to our understanding of how causal reasoning proceeds in economics. By using the research on the causes of unemployment as a case study, three questions are adressed. What are the meanings of causal claims? How can a causal claim be adequately supported by evidence? How are causal beliefs affected by incoming facts? In the process of answering these semantic, (...)
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  • Epistemology Mathematicized.John Woods - 2013 - Informal Logic 33 (2):292-331.
    Epistemology and informal logic have overlapping and broadly similar subject matters. A principle of methodological symmetry is: philosophical theories of sufficiently similar subject matters should engage similar methods. Suppose the best way to do epistemology is in highly formalized ways, with a large role for mathematical methods. The symmetry principle suggests this is also the best way to do the logic of the reasoning and argument, the subject matter of informal logic. A capitulation to mathematics is inimical to informal logicians, (...)
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  • Formal and Empirical Methods in Philosophy of Science.Vincenzo Crupi & Stephan Hartmann - 2009 - In Friedrich Stadler et al (ed.), The Present Situation in the Philosophy of Science. Springer. pp. 87--98.
    This essay addresses the methodology of philosophy of science and illustrates how formal and empirical methods can be fruitfully combined. Special emphasis is given to the application of experimental methods to confirmation theory and to recent work on the conjunction fallacy, a key topic in the rationality debate arising from research in cognitive psychology. Several other issue can be studied in this way. In the concluding section, a brief outline is provided of three further examples.
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  • Probability, confirmation, and the conjunction fallacy.Vincenzo Crupi, Branden Fitelson & Katya Tentori - 2007 - Thinking and Reasoning 14 (2):182 – 199.
    The conjunction fallacy has been a key topic in debates on the rationality of human reasoning and its limitations. Despite extensive inquiry, however, the attempt to provide a satisfactory account of the phenomenon has proved challenging. Here we elaborate the suggestion (first discussed by Sides, Osherson, Bonini, & Viale, 2002) that in standard conjunction problems the fallacious probability judgements observed experimentally are typically guided by sound assessments of _confirmation_ relations, meant in terms of contemporary Bayesian confirmation theory. Our main formal (...)
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  • (1 other version)On the Empirical Consequences of the AdS/CFT Duality.Radin Dardashti, Richard Dawid, Sean Gryb & Karim P. Y. Thebault - unknown
    We provide an analysis of the empirical consequences of the AdS/CFT duality with reference to the application of the duality in a fundamental theory, effective theory and instrumental context. Analysis of the first two contexts is intended to serve as a guide to the potential empirical and ontological status of gauge/gravity dualities as descriptions of actual physics at the Planck scale. The third context is directly connected to the use of AdS/CFT to describe real quark-gluon plasmas. In the latter context, (...)
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  • Confirmation and the generalized Nagel–Schaffner model of reduction: a Bayesian analysis.Marko Tešić - 2019 - Synthese 196 (3):1097-1129.
    In their 2010 paper, Dizadji-Bahmani, Frigg, and Hartmann argue that the generalized version of the Nagel–Schaffner model that they have developed is the right one for intertheoretic reduction, i.e. the kind of reduction that involves theories with largely overlapping domains of application. Drawing on the GNS, DFH presented a Bayesian analysis of the confirmatory relation between the reducing theory and the reduced theory and argued that, post-reduction, evidence confirming the reducing theory also confirms the reduced theory and evidence confirming the (...)
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  • Why are there descriptive norms? Because we looked for them.Ryan Muldoon, Chiara Lisciandra & Stephan Hartmann - 2014 - Synthese 191 (18):4409-4429.
    In this work, we present a mathematical model for the emergence of descriptive norms, where the individual decision problem is formalized with the standard Bayesian belief revision machinery. Previous work on the emergence of descriptive norms has relied on heuristic modeling. In this paper we show that with a Bayesian model we can provide a more general picture of the emergence of norms, which helps to motivate the assumptions made in heuristic models. In our model, the priors formalize the belief (...)
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  • The Bi-directional Relationship between Source Characteristics and Message Content.Peter J. Collins, Ulrike Hahn, Ylva von Gerber & Erik J. Olsson - 2015 - Frontiers in Psychology 9.
    Much of what we believe we know, we know through the testimony of others. While there has been long-standing evidence that people are sensitive to the characteristics of the sources of testimony, for example in the context of persuasion, researchers have only recently begun to explore the wider implications of source reliability considerations for the nature of our beliefs. Likewise, much remains to be established concerning what factors influence source reliability. In this paper, we examine, both theoretically and empirically, the (...)
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  • Lying, more or less: a computer simulation study of graded lies and trust dynamics.Borut Trpin, Anna Dobrosovestnova & Sebastian J. Götzendorfer - 2020 - Synthese 199 (1-2):1-28.
    Partial lying denotes the cases where we partially believe something to be false but nevertheless assert it with the intent to deceive the addressee. We investigate how the severity of partial lying may be determined and how partial lies can be classified. We also study how much epistemic damage an agent suffers depending on the level of trust that she invests in the liar and the severity of the lies she is told. Our analysis is based on the results from (...)
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