Results for 'Probabilism'

449 found
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  1. Probabilistic semantics for epistemic modals: Normality assumptions, conditional epistemic spaces and the strength of must and might.Guillermo Del Pinal - 2021 - Linguistics and Philosophy 45 (4):985-1026.
    The epistemic modal auxiliaries must and might are vehicles for expressing the force with which a proposition follows from some body of evidence or information. Standard approaches model these operators using quantificational modal logic, but probabilistic approaches are becoming increasingly influential. According to a traditional view, must is a maximally strong epistemic operator and might is a bare possibility one. A competing account—popular amongst proponents of a probabilisitic turn—says that, given a body of evidence, must \ entails that \\) is (...)
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  2. Are Probabilism and Special Relativity Incompatible?Nicholas Maxwell - 1985 - Philosophy of Science 52 (1):23-43.
    In this paper I expound an argument which seems to establish that probabilism and special relativity are incompatible. I examine the argument critically, and consider its implications for interpretative problems of quantum theory, and for theoretical physics as a whole.
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  3. Context Probabilism.Seth Yalcin - 2012 - In M. Aloni, Maria Aloni, Vadim Kimmelmann, Floris Roelofson, Galit W. Sassoon, Katrin Schulz & Matthijs Westera (eds.), Logic, Language, and Meaning: 18th Amsterdam Colloquium, Amsterdam, The Netherlands, December 19-21, 2011, Revised Selected Papers. Berlin: Springer. pp. 12-21.
    We investigate a basic probabilistic dynamic semantics for a fragment containing conditionals, probability operators, modals, and attitude verbs, with the aim of shedding light on the prospects for adding probabilistic structure to models of the conversational common ground.
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  4. Probabilistic Opinion Pooling.Franz Dietrich & Christian List - 2016 - In Alan Hajek & Christopher Hitchcock (eds.), Oxford Handbook of Philosophy and Probability. Oxford: Oxford University Press.
    Suppose several individuals (e.g., experts on a panel) each assign probabilities to some events. How can these individual probability assignments be aggregated into a single collective probability assignment? This article reviews several proposed solutions to this problem. We focus on three salient proposals: linear pooling (the weighted or unweighted linear averaging of probabilities), geometric pooling (the weighted or unweighted geometric averaging of probabilities), and multiplicative pooling (where probabilities are multiplied rather than averaged). We present axiomatic characterisations of each class of (...)
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  5. Probabilistic Opinion Pooling Generalized. Part One: General Agendas.Franz Dietrich & Christian List - 2017 - Social Choice and Welfare 48 (4):747–786.
    How can different individuals' probability assignments to some events be aggregated into a collective probability assignment? Classic results on this problem assume that the set of relevant events -- the agenda -- is a sigma-algebra and is thus closed under disjunction (union) and conjunction (intersection). We drop this demanding assumption and explore probabilistic opinion pooling on general agendas. One might be interested in the probability of rain and that of an interest-rate increase, but not in the probability of rain or (...)
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  6. Are Probabilism and Special Relativity Compatible?Nicholas Maxwell - 1988 - Philosophy of Science 55 (4):640-645.
    Are special relativity and probabilism compatible? Dieks argues that they are. But the possible universe he specifies, designed to exemplify both probabilism and special relativity, either incorporates a universal "now" (and is thus incompatible with special relativity), or amounts to a many world universe (which I have discussed, and rejected as too ad hoc to be taken seriously), or fails to have any one definite overall Minkowskian-type space-time structure (and thus differs drastically from special relativity as ordinarily understood). (...)
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  7. Probabilistic Arguments in the Epistemological Approach to Argumentation.Christoph Lumer - 2011 - In Frans H. Van Eemeren, Bart Garssen, David Godden & Gordon Mitchell (eds.), Proceedings of the 7th Conference of the International Society for the Study of Argumentation. Amsterdam, Netherlands: Rozenberg; Sic Sat. pp. 1141-1154.
    The aim of the paper is to develop general criteria of argumentative validity and adequacy for probabilistic arguments on the basis of the epistemological approach to argumentation. In this approach, as in most other approaches to argumentation, proabilistic arguments have been neglected somewhat. Nonetheless, criteria for several special types of probabilistic arguments have been developed, in particular by Richard Feldman and Christoph Lumer. In the first part (sects. 2-5) the epistemological basis of probabilistic arguments is discussed. With regard to the (...)
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  8. Probabilistic Representations in Perception: Are There Any, and What Would They Be?Steven Gross - 2020 - Mind and Language 35 (3):377-389.
    Nick Shea’s Representation in Cognitive Science commits him to representations in perceptual processing that are about probabilities. This commentary concerns how to adjudicate between this view and an alternative that locates the probabilities rather in the representational states’ associated “attitudes”. As background and motivation, evidence for probabilistic representations in perceptual processing is adduced, and it is shown how, on either conception, one can address a specific challenge Ned Block has raised to this evidence.
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  9. Probabilistic Causation and the Explanatory Role of Natural Selection.Pablo Razeto-Barry & Ramiro Frick - 2011 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 42 (3):344-355.
    The explanatory role of natural selection is one of the long-term debates in evolutionary biology. Nevertheless, the consensus has been slippery because conceptual confusions and the absence of a unified, formal causal model that integrates different explanatory scopes of natural selection. In this study we attempt to examine two questions: (i) What can the theory of natural selection explain? and (ii) Is there a causal or explanatory model that integrates all natural selection explananda? For the first question, we argue that (...)
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  10. Probabilistic Knowledge in Action.Carlotta Pavese - 2020 - Analysis 80 (2):342-356.
    According to a standard assumption in epistemology, if one only partially believes that p , then one cannot thereby have knowledge that p. For example, if one only partially believes that that it is raining outside, one cannot know that it is raining outside; and if one only partially believes that it is likely that it will rain outside, one cannot know that it is likely that it will rain outside. Many epistemologists will agree that epistemic agents are capable of (...)
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  11. Probabilistic Promotion and Ability.Luke Elson - 2019 - Ergo: An Open Access Journal of Philosophy 6.
    We often have some reason to do actions insofar as they promote outcomes or states of affairs, such as the satisfaction of a desire. But what is it to promote an outcome? I defend a new version of 'probabilism about promotion'. According to Minimal Probabilistic Promotion, we promote some outcome when we make that outcome more likely than it would have been if we had done something else. This makes promotion easy and reasons cheap.
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  12. A Probabilistic Analysis of Argument Cogency.David Godden & Frank Zenker - 2018 - Synthese 195 (4):1715-1740.
    This paper offers a probabilistic treatment of the conditions for argument cogency as endorsed in informal logic: acceptability, relevance, and sufficiency. Treating a natural language argument as a reason-claim-complex, our analysis identifies content features of defeasible argument on which the RSA conditions depend, namely: change in the commitment to the reason, the reason’s sensitivity and selectivity to the claim, one’s prior commitment to the claim, and the contextually determined thresholds of acceptability for reasons and for claims. Results contrast with, and (...)
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  13. Probabilistic Causation and Causal Processes: A Critique of Lewis.Peter Menzies - 1989 - Philosophy of Science 56 (4):642-663.
    This paper examines a promising probabilistic theory of singular causation developed by David Lewis. I argue that Lewis' theory must be made more sophisticated to deal with certain counterexamples involving pre-emption. These counterexamples appear to show that in the usual case singular causation requires an unbroken causal process to link cause with effect. I propose a new probabilistic account of singular causation, within the framework developed by Lewis, which captures this intuition.
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  14. Accuracy and Probabilism in Infinite Domains.Michael Nielsen - forthcoming - Mind.
    The best accuracy arguments for probabilism apply only to credence functions with finite domains, that is, credence functions that assign credence to at most finitely many propositions. This is a significant limitation. It reveals that the support for the accuracy-first program in epistemology is a lot weaker than it seems at first glance, and it means that accuracy arguments cannot yet accomplish everything that their competitors, the pragmatic (Dutch book) arguments, can. In this paper, I investigate the extent to (...)
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  15. Is Probabilistic Evidence a Source of Knowledge?Ori Friedman & John Turri - 2015 - Cognitive Science 39 (5):1062-1080.
    We report a series of experiments examining whether people ascribe knowledge for true beliefs based on probabilistic evidence. Participants were less likely to ascribe knowledge for beliefs based on probabilistic evidence than for beliefs based on perceptual evidence or testimony providing causal information. Denial of knowledge for beliefs based on probabilistic evidence did not arise because participants viewed such beliefs as unjustified, nor because such beliefs leave open the possibility of error. These findings rule out traditional philosophical accounts for why (...)
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  16. A Probabilistic Defense of Proper De Jure Objections to Theism.Brian C. Barnett - 2019
    A common view among nontheists combines the de jure objection that theism is epistemically unacceptable with agnosticism about the de facto objection that theism is false. Following Plantinga, we can call this a “proper” de jure objection—a de jure objection that does not depend on any de facto objection. In his Warranted Christian Belief, Plantinga has produced a general argument against all proper de jure objections. Here I first show that this argument is logically fallacious (it makes subtle probabilistic fallacies (...)
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  17. ‘Ramseyfying’ Probabilistic Comparativism.Edward Elliott - 2020 - Philosophy of Science 87 (4):727-754.
    Comparativism is the view that comparative confidences (e.g., being more confident that P than that Q) are more fundamental than degrees of belief (e.g., believing that P with some strength x). In this paper, I outline the basis for a new, non-probabilistic version of comparativism inspired by a suggestion made by Frank Ramsey in `Probability and Partial Belief'. I show how, and to what extent, `Ramseyan comparativism' might be used to weaken the (unrealistically strong) probabilistic coherence conditions that comparativism traditionally (...)
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  18. A Probabilistic Framework for Analysing the Compositionality of Conceptual Combinations.Peter Bruza, Kirsty Kitto, Brentyn Ramm & Laurianne Sitbon - 2015 - Journal of Mathematical Psychology 67:26-38.
    Conceptual combination performs a fundamental role in creating the broad range of compound phrases utilised in everyday language. This article provides a novel probabilistic framework for assessing whether the semantics of conceptual combinations are compositional, and so can be considered as a function of the semantics of the constituent concepts, or not. While the systematicity and productivity of language provide a strong argument in favor of assuming compositionality, this very assumption is still regularly questioned in both cognitive science and philosophy. (...)
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  19. Qualitative Probabilistic Inference Under Varied Entropy Levels.Paul D. Thorn & Gerhard Schurz - 2016 - Journal of Applied Logic 19 (2):87-101.
    In previous work, we studied four well known systems of qualitative probabilistic inference, and presented data from computer simulations in an attempt to illustrate the performance of the systems. These simulations evaluated the four systems in terms of their tendency to license inference to accurate and informative conclusions, given incomplete information about a randomly selected probability distribution. In our earlier work, the procedure used in generating the unknown probability distribution (representing the true stochastic state of the world) tended to yield (...)
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  20. A Probabilistic Analysis of Causation.Luke Glynn - 2011 - British Journal for the Philosophy of Science 62 (2):343-392.
    The starting point in the development of probabilistic analyses of token causation has usually been the naïve intuition that, in some relevant sense, a cause raises the probability of its effect. But there are well-known examples both of non-probability-raising causation and of probability-raising non-causation. Sophisticated extant probabilistic analyses treat many such cases correctly, but only at the cost of excluding the possibilities of direct non-probability-raising causation, failures of causal transitivity, action-at-a-distance, prevention, and causation by absence and omission. I show that (...)
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  21. Probabilistic Opinion Pooling Generalised. Part Two: The Premise-Based Approach.Franz Dietrich & Christian List - 2017 - Social Choice and Welfare 48 (4):787–814.
    How can different individuals' probability functions on a given sigma-algebra of events be aggregated into a collective probability function? Classic approaches to this problem often require 'event-wise independence': the collective probability for each event should depend only on the individuals' probabilities for that event. In practice, however, some events may be 'basic' and others 'derivative', so that it makes sense first to aggregate the probabilities for the former and then to let these constrain the probabilities for the latter. We formalize (...)
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  22. Probabilistic Justification Logic.Joseph Lurie - 2018 - Philosophies 3 (1):2-0.
    Justification logics are constructive analogues of modal logics. They are often used as epistemic logics, particularly as models of evidentialist justification. However, in this role, justification logics are defective insofar as they represent justification with a necessity-like operator, whereas actual evidentialist justification is usually probabilistic. This paper first examines and rejects extant candidates for solving this problem: Milnikel’s Logic of Uncertain Justifications, Ghari’s Hájek–Pavelka-Style Justification Logics and a version of probabilistic justification logic developed by Kokkinis et al. It then proposes (...)
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  23. Probabilistic Measures of Coherence and the Problem of Belief Individuation.Luca Moretti & Ken Akiba - 2007 - Synthese 154 (1):73 - 95.
    Coherentism in epistemology has long suffered from lack of formal and quantitative explication of the notion of coherence. One might hope that probabilistic accounts of coherence such as those proposed by Lewis, Shogenji, Olsson, Fitelson, and Bovens and Hartmann will finally help solve this problem. This paper shows, however, that those accounts have a serious common problem: the problem of belief individuation. The coherence degree that each of the accounts assigns to an information set (or the verdict it gives as (...)
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  24. Generalized Probabilism: Dutch Books and Accuracy Domi- Nation.J. Robert G. Williams - 2012 - Journal of Philosophical Logic 41 (5):811-840.
    Jeff Paris proves a generalized Dutch Book theorem. If a belief state is not a generalized probability then one faces ‘sure loss’ books of bets. In Williams I showed that Joyce’s accuracy-domination theorem applies to the same set of generalized probabilities. What is the relationship between these two results? This note shows that both results are easy corollaries of the core result that Paris appeals to in proving his dutch book theorem. We see that every point of accuracy-domination defines a (...)
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  25. Probabilistic Proofs, Lottery Propositions, and Mathematical Knowledge.Yacin Hamami - 2021 - Philosophical Quarterly 72 (1):77-89.
    In mathematics, any form of probabilistic proof obtained through the application of a probabilistic method is not considered as a legitimate way of gaining mathematical knowledge. In a series of papers, Don Fallis has defended the thesis that there are no epistemic reasons justifying mathematicians’ rejection of probabilistic proofs. This paper identifies such an epistemic reason. More specifically, it is argued here that if one adopts a conception of mathematical knowledge in which an epistemic subject can know a mathematical proposition (...)
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  26.  36
    Are Probabilism and Special Relativity Compatible?Nicholas Maxwell - 1988 - Philosophy of Science 55 (4):640-645.
    Are probabilism and special relativity compatible? Dieks argues that they are. But the possible universe he specifies, designed to exemplify both probabilism and special relativity, either incorporates a universal “now”, or amounts to a many world universe, or fails to have any one definite overall Minkowskian-type space-time structure. Probabilism and special relativity appear to be incompatible after all. What is at issue is not whether “the flow of time” can be reconciled with special relativity, but rather whether (...)
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  27. A Proposed Probabilistic Extension of the Halpern and Pearl Definition of ‘Actual Cause’.Luke Fenton-Glynn - 2017 - British Journal for the Philosophy of Science 68 (4):1061-1164.
    In their article 'Causes and Explanations: A Structural-Model Approach. Part I: Causes', Joseph Halpern and Judea Pearl draw upon structural equation models to develop an attractive analysis of 'actual cause'. Their analysis is designed for the case of deterministic causation. I show that their account can be naturally extended to provide an elegant treatment of probabilistic causation.
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  28. If Perception is Probabilistic, Why Doesn't It Seem Probabilistic?Ned Block - 2018 - Philosophical Transactions of the Royal Society B 373 (1755).
    The success of the Bayesian approach to perception suggests probabilistic perceptual representations. But if perceptual representation is probabilistic, why doesn't normal conscious perception reflect the full probability distributions that the probabilistic point of view endorses? For example, neurons in MT/V5 that respond to the direction of motion are broadly tuned: a patch of cortex that is tuned to vertical motion also responds to horizontal motion, but when we see vertical motion, foveally, in good conditions, it does not look at all (...)
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  29. Probabilistic Arguments for Multiple Universes.Kai Draper, Paul Draper & Joel Pust - 2007 - Pacific Philosophical Quarterly 88 (3):288–307.
    In this paper, we discuss three probabilistic arguments for the existence of multiple universes. First, we provide an analysis of total evidence and use that analysis to defend Roger White's "this universe" objection to a standard fine-tuning argument for multiple universes. Second, we explain why Rodney Holder's recent cosmological argument for multiple universes is unconvincing. Third, we develop a "Cartesian argument" for multiple universes. While this argument is not open to the objections previously noted, we show that, given certain highly (...)
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  30. Against Legal Probabilism.Martin Smith - 2021 - In Jon Robson & Zachary Hoskins (eds.), The Social Epistemology of Legal Trials. Routledge.
    Is it right to convict a person of a crime on the basis of purely statistical evidence? Many who have considered this question agree that it is not, posing a direct challenge to legal probabilism – the claim that the criminal standard of proof should be understood in terms of a high probability threshold. Some defenders of legal probabilism have, however, held their ground: Schoeman (1987) argues that there are no clear epistemic or moral problems with convictions based (...)
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  31. Does Probabilism Solve the Great Quantum Mystery?Nicholas Maxwell - 2004 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 19 (3):321-336.
    What sort of entities are electrons, photons and atoms given their wave-like and particle-like properties? Is nature fundamentally deterministic or probabilistic? Orthodox quantum theory evades answering these two basic questions by being a theory about the results of performing measurements on quantum systems. But this evasion results in OQT being a seriously defective theory. A rival, somewhat ignored strategy is to conjecture that the quantum domain is fundamentally probabilistic. This means quantum entities, interacting with one another probabilistically, must differ radically (...)
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  32. Probabilism for Stochastic Theories.Jer Steeger - 2019 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 66:34–44.
    I defend an analog of probabilism that characterizes rationally coherent estimates for chances. Specifically, I demonstrate the following accuracy-dominance result for stochastic theories in the C*-algebraic framework: supposing an assignment of chance values is possible if and only if it is given by a pure state on a given algebra, your estimates for chances avoid accuracy-dominance if and only if they are given by a state on that algebra. When your estimates avoid accuracy-dominance (roughly: when you cannot guarantee that (...)
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  33. Probabilistic Regresses and the Availability Problem for Infinitism.Adam C. Podlaskowski & Joshua A. Smith - 2014 - Metaphilosophy 45 (2):211-220.
    Recent work by Peijnenburg, Atkinson, and Herzberg suggests that infinitists who accept a probabilistic construal of justification can overcome significant challenges to their position by attending to mathematical treatments of infinite probabilistic regresses. In this essay, it is argued that care must be taken when assessing the significance of these formal results. Though valuable lessons can be drawn from these mathematical exercises (many of which are not disputed here), the essay argues that it is entirely unclear that the form of (...)
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  34. On Probabilistic Representation of Non-Probabilistic Belief Revision.Sten Lindström & Wlodek Rabinowicz - 1989 - Journal of Philosophical Logic 18 (1):69 - 101.
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  35. Cognitivist Probabilism.Paul D. Thorn - 2013 - In Vit Punochar & Petr Svarny (eds.), The Logica Yearbook 2012. College Publications. pp. 201-213.
    In this article, I introduce the term “cognitivism” as a name for the thesis that degrees of belief are equivalent to full beliefs about truth-valued propositions. The thesis (of cognitivism) that degrees of belief are equivalent to full beliefs is equivocal, inasmuch as different sorts of equivalence may be postulated between degrees of belief and full beliefs. The simplest sort of equivalence (and the sort of equivalence that I discuss here) identifies having a given degree of belief with having a (...)
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  36.  55
    Accuracy, probabilism, and the insufficiency of the alethic.Corey Dethier - 2021 - Philosophical Studies 179 (7):2285-2301.
    The best and most popular argument for probabilism is the accuracy-dominance argument, which purports to show that alethic considerations alone support the view that an agent’s degrees of belief should always obey the axioms of probability. I argue that extant versions of the accuracy-dominance argument face a problem. In order for the mathematics of the argument to function as advertised, we must assume that every omniscient credence function is classically consistent; there can be no worlds in the set of (...)
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    Purely Probabilistic Measures of Explanatory Power – A Critique.William Roche & Elliott Sober - forthcoming - Philosophy of Science:1-53.
    All extant purely probabilistic measures of explanatory power satisfy the following technical condition: if Pr(E | H1) > Pr(E | H2) and Pr(E | ~H1) < Pr(E | ~H2), then H1’s explanatory power with respect to E is greater than H2’s explanatory power with respect to E. We argue that any measure satisfying this condition faces three serious problems – the Problem of Temporal Shallowness, the Problem of Negative Causal Interactions, and the Problem of Non-Explanations. We further argue that many (...)
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  38. An Improved Probabilistic Account of Counterfactual Reasoning.Christopher G. Lucas & Charles Kemp - 2015 - Psychological Review 122 (4):700-734.
    When people want to identify the causes of an event, assign credit or blame, or learn from their mistakes, they often reflect on how things could have gone differently. In this kind of reasoning, one considers a counterfactual world in which some events are different from their real-world counterparts and considers what else would have changed. Researchers have recently proposed several probabilistic models that aim to capture how people do (or should) reason about counterfactuals. We present a new model and (...)
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  39.  23
    A Probabilistic Truth-Conditional Semantics for Indicative Conditionals.Michał Sikorski - 2022 - Semiotic Studies 35 (2):69-87.
    In my article, I present a new version of a probabilistic truth prescribing semantics for natural language indicative conditionals. The proposed truth conditions can be paraphrased as follows: an indicative conditional is true if the corresponding conditional probability is high and the antecedent is positively probabilistically relevant for the consequent or the probability of the antecedent of the conditional equals 0. In the paper, the truth conditions are defended and some of the logical properties of the proposed semantics are described.
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  40. Rational Understanding: Toward a Probabilistic Epistemology of Acceptability.Finnur Dellsén - 2019 - Synthese 198 (3):2475-2494.
    To understand something involves some sort of commitment to a set of propositions comprising an account of the understood phenomenon. Some take this commitment to be a species of belief; others, such as Elgin and I, take it to be a kind of cognitive policy. This paper takes a step back from debates about the nature of understanding and asks when this commitment involved in understanding is epistemically appropriate, or ‘acceptable’ in Elgin’s terminology. In particular, appealing to lessons from the (...)
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  41.  97
    Probabilistic Actual Causation.Fenton-Glynn Luke - manuscript
    Actual causes - e.g. Suzy's being exposed to asbestos - often bring about their effects - e.g. Suzy's suffering mesothelioma - probabilistically. I use probabilistic causal models to tackle one of the thornier difficulties for traditional accounts of probabilistic actual causation: namely probabilistic preemption.
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  42. Believing Probabilistic Contents: On the Expressive Power and Coherence of Sets of Sets of Probabilities.Catrin Campbell-Moore & Jason Konek - 2019 - Analysis Reviews:anz076.
    Moss (2018) argues that rational agents are best thought of not as having degrees of belief in various propositions but as having beliefs in probabilistic contents, or probabilistic beliefs. Probabilistic contents are sets of probability functions. Probabilistic belief states, in turn, are modeled by sets of probabilistic contents, or sets of sets of probability functions. We argue that this Mossean framework is of considerable interest quite independently of its role in Moss’ account of probabilistic knowledge or her semantics for epistemic (...)
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  43. Triviality Results For Probabilistic Modals.Goldstein Simon - 2019 - Philosophy and Phenomenological Research 99 (1):188-222.
    In recent years, a number of theorists have claimed that beliefs about probability are transparent. To believe probably p is simply to have a high credence that p. In this paper, I prove a variety of triviality results for theses like the above. I show that such claims are inconsistent with the thesis that probabilistic modal sentences have propositions or sets of worlds as their meaning. Then I consider the extent to which a dynamic semantics for probabilistic modals can capture (...)
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  44. Qualitative Probabilistic Inference with Default Inheritance.Paul D. Thorn, Christian Eichhorn, Gabriele Kern-Isberner & Gerhard Schurz - 2015 - In Christoph Beierle, Gabriele Kern-Isberner, Marco Ragni & Frieder Stolzenburg (eds.), Proceedings of the Ki 2015 Workshop on Formal and Cognitive Reasoning. pp. 16-28.
    There are numerous formal systems that allow inference of new conditionals based on a conditional knowledge base. Many of these systems have been analysed theoretically and some have been tested against human reasoning in psychological studies, but experiments evaluating the performance of such systems are rare. In this article, we extend the experiments in [19] in order to evaluate the inferential properties of c-representations in comparison to the well-known Systems P and Z. Since it is known that System Z and (...)
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  45. Preference-Based Arguments for Probabilism.David Christensen - 2001 - Philosophy of Science 68 (3):356-376.
    Both Representation Theorem Arguments and Dutch Book Arguments support taking probabilistic coherence as an epistemic norm. Both depend on connecting beliefs to preferences, which are not clearly within the epistemic domain. Moreover, these connections are standardly grounded in questionable definitional/metaphysical claims. The paper argues that these definitional/metaphysical claims are insupportable. It offers a way of reconceiving Representation Theorem arguments which avoids the untenable premises. It then develops a parallel approach to Dutch Book Arguments, and compares the results. In each case (...)
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  46. Revisiting McGee’s Probabilistic Analysis of Conditionals.John Cantwell - 2022 - Journal of Philosophical Logic (5):1-45.
    This paper calls for a re-appraisal of McGee's analysis of the semantics, logic and probabilities of indicative conditionals presented in his 1989 paper Conditional probabilities and compounds of conditionals. The probabilistic measures introduced by McGee are given a new axiomatisation built on the principle that the antecedent of a conditional is probabilistically independent of the conditional and a more transparent method of constructing such measures is provided. McGee's Dutch book argument is restructured to more clearly reveal that it introduces a (...)
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  47. Coherence and Probability: A Probabilistic Account of Coherence.Roche William - 2013 - In M. Araszkiewicz & J. Savelka (eds.), Coherence: Insights from philosophy, jurisprudence and artificial intelligence. Dordrecht: Springer. pp. 59-91.
    I develop a probabilistic account of coherence, and argue that at least in certain respects it is preferable to (at least some of) the main extant probabilistic accounts of coherence: (i) Igor Douven and Wouter Meijs’s account, (ii) Branden Fitelson’s account, (iii) Erik Olsson’s account, and (iv) Tomoji Shogenji’s account. Further, I relate the account to an important, but little discussed, problem for standard varieties of coherentism, viz., the “Problem of Justified Inconsistent Beliefs.”.
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  48. A Probabilistic Analysis of Cross-Examination Using Bayesian Networks.Marcello Di Bello - 2021 - Philosophical Issues 31 (1):41-65.
    The legal scholar Henry Wigmore asserted that cross-examination is ‘the greatest legal engine ever invented for the discovery of truth.’ Was Wigmore right? Instead of addressing this question upfront, this paper offers a conceptual ground clearing. It is difficult to say whether Wigmore was right or wrong without becoming clear about what we mean by cross-examination; how it operates at trial; what it is intended to accomplish. Despite the growing importance of legal epistemology, there is virtually no philosophical work that (...)
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    Probabilistic Inferences From Conjoined to Iterated Conditionals.Giuseppe Sanfilippo - 2018 - International Journal of Approximate Reasoning 93:103-118.
    There is wide support in logic, philosophy, and psychology for the hypothesis that the probability of the indicative conditional of natural language, $P(\textit{if } A \textit{ then } B)$, is the conditional probability of $B$ given $A$, $P(B|A)$. We identify a conditional which is such that $P(\textit{if } A \textit{ then } B)= P(B|A)$ with de Finetti's conditional event, $B|A$. An objection to making this identification in the past was that it appeared unclear how to form compounds and iterations of (...)
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  50. A Weaker Condition for Transitivity in Probabilistic Support.William A. Roche - 2012 - European Journal for Philosophy of Science 2 (1):111-118.
    Probabilistic support is not transitive. There are cases in which x probabilistically supports y , i.e., Pr( y | x ) > Pr( y ), y , in turn, probabilistically supports z , and yet it is not the case that x probabilistically supports z . Tomoji Shogenji, though, establishes a condition for transitivity in probabilistic support, that is, a condition such that, for any x , y , and z , if Pr( y | x ) > Pr( y (...)
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