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  1. How Explanation Guides Confirmation.Nevin Climenhaga - 2017 - Philosophy of Science 84 (2):359-68.
    Where E is the proposition that [If H and O were true, H would explain O], William Roche and Elliot Sober have argued that P(H|O&E) = P(H|O). In this paper I argue that not only is this equality not generally true, it is false in the very kinds of cases that Roche and Sober focus on, involving frequency data. In fact, in such cases O raises the probability of H only given that there is an explanatory connection between them.
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  • The Lottery Paradox, Knowledge, and Rationality.Dana K. Nelkin - 2000 - Philosophical Review 109 (3):373-409.
    Jim buys a ticket in a million-ticket lottery. He knows it is a fair lottery, but, given the odds, he believes he will lose. When the winning ticket is chosen, it is not his. Did he know his ticket would lose? It seems that he did not. After all, if he knew his ticket would lose, why would he have bought it? Further, if he knew his ticket would lose, then, given that his ticket is no different in its chances (...)
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  • The Structure of Epistemic Probabilities.Nevin Climenhaga - 2020 - Philosophical Studies 77 (11).
    The epistemic probability of A given B is the degree to which B evidentially supports A, or makes A plausible. This paper is a first step in answering the question of what determines the values of epistemic probabilities. I break this question into two parts: the structural question and the substantive question. Just as an object’s weight is determined by its mass and gravitational acceleration, some probabilities are determined by other, more basic ones. The structural question asks what probabilities are (...)
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  • The Inference to the Best Explanation.Gilbert H. Harman - 1965 - Philosophical Review 74 (1):88-95.
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  • An Objective Justification of Bayesianism II: The Consequences of Minimizing Inaccuracy.Hannes Leitgeb & Richard Pettigrew - 2010 - Philosophy of Science 77 (2):236-272.
    One of the fundamental problems of epistemology is to say when the evidence in an agent’s possession justifies the beliefs she holds. In this paper and its prequel, we defend the Bayesian solution to this problem by appealing to the following fundamental norm: Accuracy An epistemic agent ought to minimize the inaccuracy of her partial beliefs. In the prequel, we made this norm mathematically precise; in this paper, we derive its consequences. We show that the two core tenets of Bayesianism (...)
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  • Probabilistic Reasoning in Intelligent Systems.Judea Pearl - 1988 - Morgan Kaufmann.
    The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
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  • Putting Logic in its Place: Formal Constraints on Rational Belief.David Christensen - 2004 - Oxford University Press.
    What role, if any, does formal logic play in characterizing epistemically rational belief? Traditionally, belief is seen in a binary way - either one believes a proposition, or one doesn't. Given this picture, it is attractive to impose certain deductive constraints on rational belief: that one's beliefs be logically consistent, and that one believe the logical consequences of one's beliefs. A less popular picture sees belief as a graded phenomenon.
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  • Explanatoriness is Evidentially Irrelevant, or Inference to the Best Explanation Meets Bayesian Confirmation Theory.W. Roche & E. Sober - 2013 - Analysis 73 (4):659-668.
    In the world of philosophy of science, the dominant theory of confirmation is Bayesian. In the wider philosophical world, the idea of inference to the best explanation exerts a considerable influence. Here we place the two worlds in collision, using Bayesian confirmation theory to argue that explanatoriness is evidentially irrelevant.
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  • Inference to the Best Explanation.Peter Lipton - 1993 - Routledge/Taylor and Francis Group.
    How do we go about weighing evidence, testing hypotheses, and making inferences? The model of " inference to the best explanation " -- that we infer the hypothesis that would, if correct, provide the best explanation of the available evidence--offers a compelling account of inferences both in science and in ordinary life. Widely cited by epistemologists and philosophers of science, IBE has nonetheless remained little more than a slogan. Now this influential work has been thoroughly revised and updated, and features (...)
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  • Comparing Probabilistic Measures of Explanatory Power.Jonah N. Schupbach - 2011 - Philosophy of Science 78 (5):813-829.
    Recently, in attempting to account for explanatory reasoning in probabilistic terms, Bayesians have proposed several measures of the degree to which a hypothesis explains a given set of facts. These candidate measures of "explanatory power" are shown to have interesting normative interpretations and consequences. What has not yet been investigated, however, is whether any of these measures are also descriptive of people’s actual explanatory judgments. Here, I present my own experimental work investigating this question. I argue that one measure in (...)
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  • A Second Look at the Logic of Explanatory Power (with Two Novel Representation Theorems).Vincenzo Crupi & Katya Tentori - 2012 - Philosophy of Science 79 (3):365-385.
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  • The Logic of Explanatory Power.Jonah N. Schupbach & Jan Sprenger - 2011 - Philosophy of Science 78 (1):105-127.
    This article introduces and defends a probabilistic measure of the explanatory power that a particular explanans has over its explanandum. To this end, we propose several intuitive, formal conditions of adequacy for an account of explanatory power. Then, we show that these conditions are uniquely satisfied by one particular probabilistic function. We proceed to strengthen the case for this measure of explanatory power by proving several theorems, all of which show that this measure neatly corresponds to our explanatory intuitions. Finally, (...)
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  • Probabilistic Alternatives to Bayesianism: The Case of Explanationism.Igor Douven & Jonah N. Schupbach - 2015 - Frontiers in Psychology 6.
    There has been a probabilistic turn in contemporary cognitive science. Far and away, most of the work in this vein is Bayesian, at least in name. Coinciding with this development, philosophers have increasingly promoted Bayesianism as the best normative account of how humans ought to reason. In this paper, we make a push for exploring the probabilistic terrain outside of Bayesianism. Non-Bayesian, but still probabilistic, theories provide plausible competitors both to descriptive and normative Bayesian accounts. We argue for this general (...)
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  • Inference to the Best Explanation Versus Bayes’s Rule in a Social Setting.Igor Douven & Sylvia Wenmackers - 2017 - British Journal for the Philosophy of Science 68 (2).
    This article compares inference to the best explanation with Bayes’s rule in a social setting, specifically, in the context of a variant of the Hegselmann–Krause model in which agents not only update their belief states on the basis of evidence they receive directly from the world, but also take into account the belief states of their fellow agents. So far, the update rules mentioned have been studied only in an individualistic setting, and it is known that in such a setting (...)
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  • The Stanford Encyclopedia of Philosophy.Edward N. Zalta (ed.) - 2004 - Stanford, CA: The Metaphysics Research Lab.
    The Stanford Encyclopedia of Philosophy is an open access, dynamic reference work designed to organize professional philosophers so that they can write, edit, and maintain a reference work in philosophy that is responsive to new research. From its inception, the SEP was designed so that each entry is maintained and kept up to date by an expert or group of experts in the field. All entries and substantive updates are refereed by the members of a distinguished Editorial Board before they (...)
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  • Accuracy, Coherence, and Evidence.Branden Fitelson & Kenny Easwaran - 2015 - Oxford Studies in Epistemology 5:61-96.
    Taking Joyce’s (1998; 2009) recent argument(s) for probabilism as our point of departure, we propose a new way of grounding formal, synchronic, epistemic coherence requirements for (opinionated) full belief. Our approach yields principled alternatives to deductive consistency, sheds new light on the preface and lottery paradoxes, and reveals novel conceptual connections between alethic and evidential epistemic norms.
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  • Laws and Symmetry.Bas C. van Fraassen - 1989 - Oxford University Press.
    Metaphysicians speak of laws of nature in terms of necessity and universality; scientists, in terms of symmetry and invariance. In this book van Fraassen argues that no metaphysical account of laws can succeed. He analyzes and rejects the arguments that there are laws of nature, or that we must believe there are, and argues that we should disregard the idea of law as an adequate clue to science. After exploring what this means for general epistemology, the author develops the empiricist (...)
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  • Inference to the Best Explanation.Jonathan Vogel - 1993 - Philosophical Review 102 (3):419.
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  • Naive and Refined Truth Approximation.Theo A. F. Kuipers - 1992 - Synthese 93 (3):299 - 341.
    The naive structuralist definition of truthlikeness is an idealization in the sense that it assumes that all mistaken models of a theory are equally bad. The natural concretization is a refined definition based on an underlying notion of structurelikeness.In Section 1 the naive definition of truthlikeness of theories is presented, using a new conceptual justification, in terms of instantial and explanatory mistakes.
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  • Locating IBE in the Bayesian Framework.Jonathan Weisberg - 2009 - Synthese 167 (1):125-143.
    Inference to the Best Explanation (IBE) and Bayesianism are our two most prominent theories of scientific inference. Are they compatible? Van Fraassen famously argued that they are not, concluding that IBE must be wrong since Bayesianism is right. Writers since then, from both the Bayesian and explanationist camps, have usually considered van Fraassen’s argument to be misguided, and have plumped for the view that Bayesianism and IBE are actually compatible. I argue that van Fraassen’s argument is actually not so misguided, (...)
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  • Inference to the Best Explanation, Dutch Books, and Inaccuracy Minimisation.Igor Douven - 2013 - Philosophical Quarterly 63 (252):428-444.
    Bayesians have traditionally taken a dim view of the Inference to the Best Explanation, arguing that, if IBE is at variance with Bayes ' rule, then it runs afoul of the dynamic Dutch book argument. More recently, Bayes ' rule has been claimed to be superior on grounds of conduciveness to our epistemic goal. The present paper aims to show that neither of these arguments succeeds in undermining IBE.
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  • The Role of Explanatory Considerations in Updating.Igor Douven & Jonah N. Schupbach - 2015 - Cognition 142:299-311.
    There is an ongoing controversy in philosophy about the connection between explanation and inference. According to Bayesians, explanatory considerations should be given weight in determining which inferences to make, if at all, only insofar as doing so is compatible with Strict Conditionalization. Explanationists, on the other hand, hold that explanatory considerations can be relevant to the question of how much confidence to invest in our hypotheses in ways which violate Strict Conditionalization. The controversy has focused on normative issues. This paper (...)
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  • Inference to the Best Explanation Made Coherent.Igor Douven - 1999 - Philosophy of Science 66 (Supplement):S424-S435.
    Van Fraassen (1989) argues that Inference to the Best Explanation is incoherent in the sense that adopting it as a rule for belief change will make one susceptible to a dynamic Dutch book. The present paper argues against this. A strategy is described that allows us to infer to the best explanation free of charge.
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  • The Structure and Dynamics of Scientific Theories: A Hierarchical Bayesian Perspective.Leah Henderson, Noah D. Goodman, Joshua B. Tenenbaum & James F. Woodward - 2010 - Philosophy of Science 77 (2):172-200.
    Hierarchical Bayesian models (HBMs) provide an account of Bayesian inference in a hierarchically structured hypothesis space. Scientific theories are plausibly regarded as organized into hierarchies in many cases, with higher levels sometimes called ‘paradigms’ and lower levels encoding more specific or concrete hypotheses. Therefore, HBMs provide a useful model for scientific theory change, showing how higher‐level theory change may be driven by the impact of evidence on lower levels. HBMs capture features described in the Kuhnian tradition, particularly the idea that (...)
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  • Truthlikeness.Graham Oddie - 2014 - Stanford Encyclopedia.
    Truth is the aim of inquiry. Nevertheless, some falsehoods seem to realize this aim better than others. Some truths better realize the aim than other truths. And perhaps even some falsehoods realize the aim better than some truths do. The dichotomy of the class of propositions into truths and falsehoods should thus be supplemented with a more fine-grained ordering — one which classifies propositions according to their closeness to the truth, their degree of truthlikeness or verisimilitude. The logical problem of (...)
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  • Relativism and Realism in Science.Robert Nola (ed.) - 1988 - Kluwer Academic Publishers.
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  • Against Conditionalization.Fahiem Bacchus, Henry E. Kyburg Jr & Mariam Thalos - 1990 - Synthese 85 (3):475 - 506.
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  • Experience and Perceptual Belief.Alan Musgrave - 2009 - In Zuzana Parusniková & R. S. Cohen (eds.), Rethinking Popper. Springer. pp. 5--19.
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  • Concise Routledge Encyclopedia of Philosophy. Routledge - 2000
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  • Approaching the Truth With the Rule of Success.Theo Kuipers - 1984 - Philosophia Naturalis 21 (2/4):244-253.
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  • Inference to the Best Explanation.David Kinght - 1992 - Philosophical Books 33 (3):191-192.
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  • Inference to the Best Explanation and Bayesianism.Stathis Psillos - 2004 - Vienna Circle Institute Yearbook 11:83-91.
    Niiniluoto has offered an incisive and comprehensive review of the recent debates about abduction. There is little on which I disagree with him. So, in this commentary, I shall try to cast some doubts to the attempts to render Inference to the Best Explanation within a Bayesian framework.
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