About this topic
Summary Bayesian Reasoning includes issues related to: 1. the probabilistic logic of evidential support for hypotheses;  2. the logic of comparative belief, belief strengths, and belief updating as represented by classical probability functions; 3. the logic of decision as represented in terms of utilities, probabilities, and expected utility maximization, including ways in which this logic may represent comparative preferences among acts or states of affairs; 4. Bayesian probabilistic treatments of causal influence (e.g. via Bayes nets); 5. studies of relationships between human performance and models of reasoning and decision of a Bayesian kind (as described in 1-4 above).
Key works

Bayesian reasoning includes a wide variety of topics and issues. For introductory overviews of Bayesian confirmation theory and decision theory, among the best texts available are Skyrms 1966 and Hacking 2001; at a somewhat more advanced level Urbach & Howson 1993 is essential reading. Key sources for Bayesian probability and decision theory include Ramsey 1926Savage 1954Jeffrey 1965, and Joyce 1999. The classic treatment of Bayes nets is Pearl 1988Chater & Oaksford 2008 is an excellent collection of articles on Bayesian modeling of natural human reasoning. Also see the Stanford Encyclopedia of Philosophy (online, Zalta 2014) for helpful articles on various aspects of Bayesian reasoning: e.g. on Bayes' Theorem, Bayesian Epistemology, Inductive Logic, Decision Theory, etc.

Introductions Hájek 2007; Joyce 2008; Hawthorne 2011; Talbott 2006; Vineberg 2011; Weirich 2009; Hitchcock 2008.
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  1. Rational updating at the crossroads.Silvia Milano & Andrés Perea - 2024 - Economics and Philosophy 40 (1):190-211.
    In this paper we explore the absentminded driver problem using two different scenarios. In the first scenario we assume that the driver is capable of reasoning about his degree of absentmindedness before he hits the highway. This leads to a Savage-style model where the states are mutually exclusive and the act-state independence is in place. In the second we employ centred possibilities, by modelling the states (i.e. the events about which the driver is uncertain) as the possible final destinations indexed (...)
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  2. Suspension of judgment, non-additivity, and additivity of possibilities.Aldo Filomeno - forthcoming - Acta Analytica.
    In situations where we ignore everything but the space of possibilities, we ought to suspend judgment—that is, remain agnostic—about which of these possibilities is the case. This means that we cannot sum our degrees of belief in different possibilities, something that has been formalized as an axiom of non-additivity. Consistent with this way of representing our ignorance, I defend a doxastic norm that recommends that we should nevertheless follow a certain additivity of possibilities: even if we cannot sum degrees of (...)
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  3. Học liệu BMF analytics hiện diện tại Harvard University HOLLIS.Tổ Kỹ Thuật Aisdl - 2024 - Bmf Method.
    Cuốn tài liệu học thuật trình bày phương pháp “BMF analytics” hiện đã bước sang năm thứ ba phục vụ cộng đồng nghiên cứu. Cuốn sách đã góp phần hỗ trợ nhiều nhà nghiên cứu trẻ triển khai và hoàn thành công việc.
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  4. The BMF analytics title at Harvard University HOLLIS.A. I. S. D. L. Team - 2024 - Sm3D.
    The methodology title on BMF analytics is now in its third year of service to our research community, enabling many researchers to implement their research pursuits.
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  5. The Chances of Choices.Reuben Stern - forthcoming - British Journal for the Philosophy of Science.
    It is sometimes thought that if we treat decision-theoretic options as interventions, then we can use evidential decision theory to vindicate causal dominance reasoning. This is supposed to be guaranteed by a causal modeling axiom that implies that interventions are probabilistically independent of their non-effects---namely, the Causal Markov Condition. But there are two concerns for this line of reasoning. First, the Causal Markov Condition doesn’t imply that an agent should regard their intervention as probabilistically independent from its non-effects when the (...)
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  6. Cuộc thảo luận kỳ quặc của 3 ông bói cá.P. V. Chẫu Quê - 2024 - Bayesvl 2..
    Đến khúc này, 3 ông bói cá cũng bí nên chuyển chủ đề. Hướng sang vấn đề ăn cá vậy. Đây là vấn đề truyền thống lâu đời. Có chuyện gì lớn?
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  7. The Epistemic and the Deontic Preface Paradox.Lina M. Lissia & Jan Sprenger - manuscript
    This paper generalizes the (epistemic) preface paradox beyond the principle of belief aggregation and constructs a similar paradox for deontic reasoning. The analysis of the deontic case yields a solution strategy---restricting belief/obligation aggregation rather than giving it up altogether---that can be transferred to the epistemic case. Our proposal amounts to a reasonable compromise between two goals: (i) sticking to bridge principles between evidence and belief, such as the Lockean Thesis, and (ii) obtaining a sufficiently strong logic of doxastic and deontic (...)
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  8. ‘Stargazing’ and p-hacking behaviours in social sciences: some insights from a developing country.Quan-Hoang Vuong, Tung Manh Ho & Phuong Viet La - 2019 - European Science Editing 45 (2):54-55.
    The persistence of “stargazing,” p-hacking and HARKing4 are among the main causes for the severity of the irreproducibility problem in social sciences.
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  9. Bayesians Commit the Gambler's Fallacy.Kevin Dorst - manuscript
    The gambler’s fallacy is the tendency to expect random processes to switch more often than they actually do—for example, to think that after a string of tails, a heads is more likely. It’s often taken to be evidence for irrationality. It isn’t. Rather, it’s to be expected from a group of Bayesians who begin with causal uncertainty, and then observe unbiased data from an (in fact) statistically independent process. Although they converge toward the truth, they do so in an asymmetric (...)
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  10. Sơ kết năm 2023 của bayesvl.Hannah Chau - 2024 - Bayesvl.
    Trưa ngày 1-1 năm mới, R Documentation cho biết mức downloads tạm tính của chương trình bayesvl trong tháng 12-2023. Hiện đang đứng ở mức 157, tháng thấp nhất trong năm.
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  11. Realism and instrumentalism in Bayesian cognitive science.Danielle Williams & Zoe Drayson - 2024 - In Tony Cheng, Ryoji Sato & Jakob Hohwy (eds.), Expected Experiences: The Predictive Mind in an Uncertain World. Routledge.
    There are two distinct approaches to Bayesian modelling in cognitive science. Black-box approaches use Bayesian theory to model the relationship between the inputs and outputs of a cognitive system without reference to the mediating causal processes; while mechanistic approaches make claims about the neural mechanisms which generate the outputs from the inputs. This paper concerns the relationship between these two approaches. We argue that the dominant trend in the philosophical literature, which characterizes the relationship between black-box and mechanistic approaches to (...)
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  12. Tác động của việc giới thiệu bayesvl qua chương trình VIASM HANU lên lượng tải về.Nguyễn Phương Tri - 2023 - Bmf Analytics.
    Từ thực tế dữ liệu, có thể thấy nếu như mức độ quan tâm ứng dụng thực sự của BMF analytics cho công việc trở nên phổ biến, thì khả năng bayesvl sẽ được tải về và sử dụng sẽ có nhiều cơ hội để cải thiện.
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  13. BMF Analytics Training Course at VIASM HANU Conference.A. I. S. D. L. Team - 2023 - Viasm-Hanu.
    On November 3 and 4, 2023, Dr. Nguyen Minh Hoang (Phenikaa University), co-author of the BMF Analytics [1], gave a lecture on computational approaches using bayesvl and BMF application for social science research.
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  14. BMF tại khóa học VIASM HANU.Chẫu Chàng - 2023 - Bmf.
    TS. Nguyễn Minh Hoàng (ĐH Phenikaa), đã giảng bài về tiếp cận tính toán sử dụng bayesvl và ứng dụng BMF cho công việc nghiên cứu KHXH.
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  15. Slurs' Variability, Emotional Dimensions, and Game-Theoretic Pragmatics.Víctor Carranza-Pinedo - 2023 - In D. Bekki, K. Mineshima & E. McCready (eds.), Logic and Engineering of Natural Language Semantics. LENLS 2022. Cham: Springer.
    Slurs’ meaning is highly unstable. A slurring utterance like ‘Hey, F, where have you been?’ (where F is a slur) may receive a wide array of interpretations depending on various contextual factors such as the speaker’s social identity, their relationship to the target group, tone of voice, and more. Standard semantic, pragmatic, and non-content theories of slurs have proposed different mechanisms to account for some or all types of variability observed, but without providing a unified framework that allows us to (...)
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  16. Waarom we beter denken dan we denken.Maarten van Doorn - 2023 - Noordboek Uitgeverij.
    Genomineerd voor de Socratesbeker 2024. De mens is irrationeel. Verliefd op zijn eigen gelijk. Doof voor feiten argumenten. Verblind door honderden denkfouten. Een makkelijke prooi voor nepnieuws. Gevangen in filterbubbels. Zo is het heersende idee. Maar klopt het wel? In dit boek verweeft filosoof Maarten van Doorn de jongste inzichten uit de psychologie, communicatiewetenschappen, filosofie en politicologie. Hij neemt ons mee op een reis langs verrassende onderzoeksresultaten en scherpzinnige filosofen en geeft nieuwe antwoorden op dringende vragen: Waarom geloven we wat (...)
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  17. Towards an empirically informed normative Bayesian scheme-based account of argument from expert opinion.Kong Ngai Pei & Chin Shing Arthur Chin - 2023 - Thinking and Reasoning 29 (4):726-759.
    This article seeks, first, to show that much of the existing normative work on argument from expert opinion (AEO) is problematic for failing to be properly informed by empirical findings on expert performance. Second, it seeks to show how, with the analytic tool of Bayesian reasoning, the problem diagnosed can be remedied to circumvent some of the problems facing the scheme-based treatment of AEOs. To establish the first contention, we will illustrate how empirical studies on factors conditioning expert reliability can (...)
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  18. Trivalent Conditionals: Stalnaker's Thesis and Bayesian Inference.Paul Égré, Lorenzo Rossi & Jan Sprenger - manuscript
    This paper develops a trivalent semantics for indicative conditionals and extends it to a probabilistic theory of valid inference and inductive learning with conditionals. On this account, (i) all complex conditionals can be rephrased as simple conditionals, connecting our account to Adams's theory of p-valid inference; (ii) we obtain Stalnaker's Thesis as a theorem while avoiding the well-known triviality results; (iii) we generalize Bayesian conditionalization to an updating principle for conditional sentences. The final result is a unified semantic and probabilistic (...)
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  19. Center Indifference and Skepticism.David Builes - forthcoming - Noûs.
    Many philosophers have been attracted to a restricted version of the principle of indifference in the case of self-locating belief. Roughly speaking, this principle states that, within any given possible world, one should be indifferent between different hypotheses concerning who one is within that possible world, so long as those hypotheses are compatible with one’s evidence. My first goal is to defend a more precise version of this principle. After responding to several existing criticisms of such a principle, I argue (...)
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  20. Rational Aversion to Information.Sven Neth - forthcoming - British Journal for the Philosophy of Science.
    Is more information always better? Or are there some situations in which more information can make us worse off? Good (1967) argues that expected utility maximizers should always accept more information if the information is cost-free and relevant. But Good's argument presupposes that you are certain you will update by conditionalization. If we relax this assumption and allow agents to be uncertain about updating, these agents can be rationally required to reject free and relevant information. Since there are good reasons (...)
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  21. Learning from experience and conditionalization.Peter Brössel - 2023 - Philosophical Studies 180 (9):2797-2823.
    Bayesianism can be characterized as the following twofold position: (i) rational credences obey the probability calculus; (ii) rational learning, i.e., the updating of credences, is regulated by some form of conditionalization. While the formal aspect of various forms of conditionalization has been explored in detail, the philosophical application to learning from experience is still deeply problematic. Some philosophers have proposed to revise the epistemology of perception; others have provided new formal accounts of conditionalization that are more in line with how (...)
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  22. Credal imprecision and the value of evidence.Nilanjan Das - 2023 - Noûs 57 (3):684-721.
    This paper is about a tension between two theses. The first is Value of Evidence: roughly, the thesis that it is always rational for an agent to gather and use cost‐free evidence for making decisions. The second is Rationality of Imprecision: the thesis that an agent can be rationally required to adopt doxastic states that are imprecise, i.e., not representable by a single credence function. While others have noticed this tension, I offer a new diagnosis of it. I show that (...)
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  23. The Myside Bias in Argument Evaluation: A Bayesian Model.Edoardo Baccini & Stephan Hartmann - 2022 - Proceedings of the Annual Meeting of the Cognitive Science Society 44:1512-1518.
    The "myside bias'' in evaluating arguments is an empirically well-confirmed phenomenon that consists of overweighting arguments that endorse one's beliefs or attack alternative beliefs while underweighting arguments that attack one's beliefs or defend alternative beliefs. This paper makes two contributions: First, it proposes a probabilistic model that adequately captures three salient features of myside bias in argument evaluation. Second, it provides a Bayesian justification of this model, thus showing that myside bias has a rational Bayesian explanation under certain conditions.
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  24. Confirmation, Coherence and the Strength of Arguments.Stephan Hartmann & Borut Trpin - 2023 - Proceedings of the Annual Meeting of the Cognitive Science Society 45:1473-1479.
    Alongside science and law, argumentation is also of central importance in everyday life. But what characterizes a good argument? This question has occupied philosophers and psychologists for centuries. The theory of Bayesian argumentation is particularly suitable for clarifying it, because it allows us to take into account in a natural way the role of uncertainty, which is central to much argumentation. Moreover, it offers the possibility of measuring the strength of an argument in probabilistic terms. One way to do this, (...)
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  25. Cao điểm bayesvl chỉ có rau...Bên Dòng Mê-Kông - 2023 - Bayesvl.
    Cao điểm bayesvl chỉ có rau... -/- Người ta bẩu, ăn thịt/cá mới đủ protein để phục vụ suy nghĩ.
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  26. bayesvl was made of... salad. A lot of it, really.Viet-Phuong La - 2023 - Sm3D Bayesvl.
    An untold aspect of the inexpensiveness of bayesvl was that its developers also ate very little, mostly vegetables.
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  27. Lượng download của bayesvl qua 2 năm.A. I. S. D. L. Team - 2023 - Aisdl Computing.
    Như vậy, tổng lượng downloads của bayesvl bản 0.8.5 từ các servers CRAN giai đoạn tháng 7-2021 tới tháng 6-2023 đạt 7930. (Số thống kê này không bao gồm lượng downloads từ Github, như đã nêu trên.).
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  28. Belief expansion, contextual fit and the reliability of information sources.Luc Bovens & Stephan Hartmann - 2001 - In Varol Akman (ed.), Modeling and Using Context. pp. 421-424.
    We develop a probabilistic criterion for belief expansion that is sensitive to the degree of contextual fit of the new information to our belief set as well as to the reliability of our information source. We contrast our approach with the success postulate in AGM-style belief revision and show how the idealizations in our approach can be relaxed by invoking Bayesian-Network models.
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  29. Edenic Orgulity.Gordon Belot - manuscript
    The orgulity objection of Belot (2013) is recast in the form of a decision problem.
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  30. The mindsponge & BMF analytics project.Aisdl Team - 2023 - Sm3D Science Portal.
    We aim to support researchers in social sciences and humanities in conducting and publishing their studies on a global scale, especially Early Career Researchers (ECRs) and those in low-resource settings. For that purpose, AISDL created the Science Portal for the Serendipity-Mindsponge-3D (SM3D) Knowledge Management Theory.
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  31. Natural Theology and Divine Freedom.Philipp Kremers - forthcoming - Sophia:1-16.
    Many philosophers of theistic religions claim (1) that there are powerful a posteriori arguments for God’s existence that make it rational to believe that He exists and at the same time maintain (2) that God always has the freedom to do otherwise. In this article, I argue that these two positions are inconsistent because the empirical evidence on which the a posteriori arguments for God’s existence rest can be explained better by positing the existence of a God-like being without the (...)
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  32. An Improved Argument for Superconditionalization.Julia Staffel & Glauber De Bona - forthcoming - Erkenntnis:1-27.
    Standard arguments for Bayesian conditionalizing rely on assumptions that many epistemologists have criticized as being too strong: (i) that conditionalizers must be logically infallible, which rules out the possibility of rational logical learning, and (ii) that what is learned with certainty must be true (factivity). In this paper, we give a new factivity-free argument for the superconditionalization norm in a personal possibility framework that allows agents to learn empirical and logical falsehoods. We then discuss how the resulting framework should be (...)
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  33. bayesvl: Visually learning the graphical structure of Bayesian networks and performing MCMC with ‘Stan’.Viet-Phuong La & Quan-Hoang Vuong - 2019 - Vienna, Austria: The Comprehensive R Archive Network (CRAN).
    La, V. P., & Vuong, Q. H. (2019). bayesvl: Visually learning the graphical structure of Bayesian networks and performing MCMC with ‘Stan’. The Comprehensive R Archive Network (CRAN).
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  34. Extrapolating from experiments, confidently.Donal Khosrowi - 2023 - European Journal for Philosophy of Science 13 (2):1-28.
    Extrapolating causal effects from experiments to novel populations is a common practice in evidence-based-policy, development economics and other social science areas. Drawing on experimental evidence of policy effectiveness, analysts aim to predict the effects of policies in new populations, which might differ importantly from experimental populations. Existing approaches made progress in articulating the sorts of similarities one needs to assume to enable such inferences. It is also recognized, however, that many of these assumptions will remain surrounded by significant uncertainty in (...)
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  35. Updating incoherent credences ‐ Extending the Dutch strategy argument for conditionalization.Glauber De Bona & Julia Staffel - 2021 - Philosophy and Phenomenological Research 105 (2):435-460.
    In this paper, we ask: how should an agent who has incoherent credences update when they learn new evidence? The standard Bayesian answer for coherent agents is that they should conditionalize; however, this updating rule is not defined for incoherent starting credences. We show how one of the main arguments for conditionalization, the Dutch strategy argument, can be extended to devise a target property for updating plans that can apply to them regardless of whether the agent starts out with coherent (...)
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  36. Why Subjectivism?Chloé de Canson - manuscript
    In response to two trenchant objections, radical subjective Bayesianism has been widely rejected. In this paper, I seek, if not to rehabilitate subjectivism, at least to show its critic what is attractive about the position. I argue that what is at stake in the subjectivism/anti-subjectivism debate is not, as is commonly thought, which norms of rationality are true, but rather, the conception of rationality that we adopt: there is an alternative approach to the widespread telic approach to rationality, which I (...)
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  37. The Nature of Awareness Growth.Chloé de Canson - forthcoming - Philosophical Review.
    Awareness growth—coming to entertain propositions of which one was previously unaware—is a crucial aspect of epistemic thriving. And yet, it is widely believed that orthodox Bayesianism cannot accommodate this phenomenon, since that would require employing supposedly defective catch-all propositions. Orthodox Bayesianism, it is concluded, must be amended. In this paper, I show that this argument fails, and that, on the contrary, the orthodox version of Bayesianism is particularly well-suited to accommodate awareness growth. For it entails what I call the refinement (...)
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  38. Book Review: Being You: A New Science of Consciousness by Anil Seth.Tung Manh Ho - 2022 - LSE Impact of Social Science.
    In Being You, Anil Seth takes us on a comprehensive tour through the science of consciousness, drawing on the most up-to-date data, lessons and theories in the field. This is a compelling book that will leave readers pondering whether new technologies and smart experimental designs will further deepen our understanding of the mind, writes Manh Tung Ho.
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  39. The Father of Faith Rationally Reconstructed.Levi Durham - 2022 - Faith and Philosophy 39 (2):272-290.
    There is a tension for those who want to simultaneously hold that Abraham’s disposition to sacrifice Isaac is epistemically justified and yet hold that a contemporary father would not be justified in believing that God is commanding him to sacrifice his son. This paper attempts to resolve that tension. While some commentators have correctly pointed out that one must take Abraham’s long relationship with God into account when considering Abraham’s readiness to sacrifice his son, they do not entertain the possibility (...)
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  40. Précis for Unsettled Thoughts.Julia Staffel - 2022 - Philosophical Studies 179 (10):3151-3154.
    This précis gives a brief summary of the key points of Julia Staffel’s book Unsettled Thoughts.
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  41. Comparative Opinion Loss.Benjamin Eva & Reuben Stern - 2022 - Philosophy and Phenomenological Research 107 (3):613-637.
    It is a consequence of the theory of imprecise credences that there exist situations in which rational agents inevitably become less opinionated toward some propositions as they gather more evidence. The fact that an agent's imprecise credal state can dilate in this way is often treated as a strike against the imprecise approach to inductive inference. Here, we show that dilation is not a mere artifact of this approach by demonstrating that opinion loss is countenanced as rational by a substantially (...)
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  42. Distention for Sets of Probabilities.Rush T. Stewart & Michael Nielsen - 2022 - Philosophy of Science 89 (3):604-620.
    Bayesians often appeal to “merging of opinions” to rebut charges of excessive subjectivity. But what happens in the short run is often of greater interest than what happens in the limit. Seidenfeld and coauthors use this observation as motivation for investigating the counterintuitive short run phenomenon of dilation, since, they allege, dilation is “the opposite” of asymptotic merging of opinions. The measure of uncertainty relevant for dilation, however, is not the one relevant for merging of opinions. We explicitly investigate the (...)
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  43. On the Best Accuracy Arguments for Probabilism.Michael Nielsen - 2022 - Philosophy of Science 89 (3):621-630.
    In a recent paper, Pettigrew reports a generalization of the celebrated accuracy-dominance theorem due to Predd et al., but Pettigrew’s proof is incorrect. I will explain the mistakes and provide a correct proof.
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  44. Empirical evidence for moral Bayesianism.Haim Cohen, Ittay Nissan-Rozen & Anat Maril - forthcoming - Philosophical Psychology.
    Many philosophers in the field of meta-ethics believe that rational degrees of confidence in moral judgments should have a probabilistic structure, in the same way as do rational degrees of belief. The current paper examines this position, termed “moral Bayesianism,” from an empirical point of view. To this end, we assessed the extent to which degrees of moral judgments obey the third axiom of the probability calculus, ifP(A∩B)=0thenP(A∪B)=P(A)+P(B), known as finite additivity, as compared to degrees of beliefs on the one (...)
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  45. Bayesian merging of opinions and algorithmic randomness.Francesca Zaffora Blando - forthcoming - British Journal for the Philosophy of Science.
    We study the phenomenon of merging of opinions for computationally limited Bayesian agents from the perspective of algorithmic randomness. When they agree on which data streams are algorithmically random, two Bayesian agents beginning the learning process with different priors may be seen as having compatible beliefs about the global uniformity of nature. This is because the algorithmically random data streams are of necessity globally regular: they are precisely the sequences that satisfy certain important statistical laws. By virtue of agreeing on (...)
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  46. Genericity and Inductive Inference.Henry Ian Schiller - forthcoming - Philosophy of Science:1-18.
    We are often justified in acting on the basis of evidential confirmation. I argue that such evidence supports belief in non-quantificational generic generalizations, rather than universally quantified generalizations. I show how this account supports, rather than undermines, a Bayesian account of confirmation. Induction from confirming instances of a generalization to belief in the corresponding generic is part of a reasoning instinct that is typically (but not always) correct, and allows us to approximate the predictions that formal epistemology would make.
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  47. Diachronic and Interpersonal Coherence.Kenny Easwaran & Reuben Stern - forthcoming - In A. K. Flowerree & Baron Reed (eds.), Towards an Expansive Epistemology: Norms, Action, and the Social Sphere. Routledge.
    Bayesians standardly claim that there is rational pressure for agents’ credences to cohere across time because they face bad (epistemic or practical) consequences if they fail to diachronically cohere. But as David Christensen has pointed out, groups of individual agents also face bad consequences if they fail to interpersonally cohere, and there is no general rational pressure for one agent's credences to cohere with another’s. So it seems that standard Bayesian arguments may prove too much. Here, we agree with Christensen (...)
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  48. Probabilistic stability, agm revision operators and maximum entropy.Krzysztof Mierzewski - 2020 - Review of Symbolic Logic:1-38.
    Several authors have investigated the question of whether canonical logic-based accounts of belief revision, and especially the theory of AGM revision operators, are compatible with the dynamics of Bayesian conditioning. Here we show that Leitgeb's stability rule for acceptance, which has been offered as a possible solution to the Lottery paradox, allows to bridge AGM revision and Bayesian update: using the stability rule, we prove that AGM revision operators emerge from Bayesian conditioning by an application of the principle of maximum (...)
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  49. Inference to the Best Explanation - An Overview.Frank Cabrera - 2022 - In Lorenzo Magnani (ed.), Handbook of Abductive Cognition. Cham: Springer. pp. 1-34.
    In this article, I will provide a critical overview of the form of non-deductive reasoning commonly known as “Inference to the Best Explanation” (IBE). Roughly speaking, according to IBE, we ought to infer the hypothesis that provides the best explanation of our evidence. In section 2, I survey some contemporary formulations of IBE and highlight some of its putative applications. In section 3, I distinguish IBE from C.S. Peirce’s notion of abduction. After underlining some of the essential elements of IBE, (...)
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  50. Deliberation and confidence change.Nora Heinzelmann & Stephan Hartmann - 2022 - Synthese 200 (1):1-13.
    We argue that social deliberation may increase an agent’s confidence and credence under certain circumstances. An agent considers a proposition H and assigns a probability to it. However, she is not fully confident that she herself is reliable in this assignment. She then endorses H during deliberation with another person, expecting him to raise serious objections. To her surprise, however, the other person does not raise any objections to H. How should her attitudes toward H change? It seems plausible that (...)
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