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  1. (3 other versions)Vision: Variations on Some Berkeleian Themes.Robert Schwartz & David Marr - 1985 - Philosophical Review 94 (3):411.
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  • Erratum: Probabilities of Conditionals and Conditional Probabilities.David Lewis - 1976 - Philosophical Review 85 (4):561.
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  • Structured statistical models of inductive reasoning.Charles Kemp & Joshua B. Tenenbaum - 2009 - Psychological Review 116 (1):20-58.
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  • Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment.Amos Tversky & Daniel Kahneman - 1983 - Psychological Review 90 (4):293-315.
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  • Word learning as Bayesian inference.Fei Xu & Joshua B. Tenenbaum - 2007 - Psychological Review 114 (2):245-272.
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  • Philosophical Theories of Probability.Donald Gillies - 2000 - New York: Routledge.
    The Twentieth Century has seen a dramatic rise in the use of probability and statistics in almost all fields of research. This has stimulated many new philosophical ideas on probability. _Philosophical Theories of Probability_ is the first book to present a clear, comprehensive and systematic account of these various theories and to explain how they relate to one another. Gillies also offers a distinctive version of the propensity theory of probability, and the intersubjective interpretation, which develops the subjective theory.
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  • Probabilistic models of language processing and acquisition.Nick Chater & Christopher D. Manning - 2006 - Trends in Cognitive Sciences 10 (7):335–344.
    Probabilistic methods are providing new explanatory approaches to fundamental cognitive science questions of how humans structure, process and acquire language. This review examines probabilistic models defined over traditional symbolic structures. Language comprehension and production involve probabilistic inference in such models; and acquisition involves choosing the best model, given innate constraints and linguistic and other input. Probabilistic models can account for the learning and processing of language, while maintaining the sophistication of symbolic models. A recent burgeoning of theoretical developments and online (...)
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  • (1 other version)Letting structure emerge: connectionist and dynamical systems approaches to cognition.James L. McClelland, Matthew M. Botvinick, David C. Noelle, David C. Plaut, Timothy T. Rogers, Mark S. Seidenberg & Linda B. Smith - 2010 - Trends in Cognitive Sciences 14 (8):348-356.
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  • Bayesian decision theory in sensorimotor control.Konrad P. Körding & Daniel M. Wolpert - 2006 - Trends in Cognitive Sciences 10 (7):319-326.
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  • (1 other version)Bayes or Bust?: A Critical Examination of Bayesian Confirmation Theory.John Earman - 1992 - MIT Press.
    There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes’s original paper to contemporary formal learning theory.In (...)
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  • Bayesian Epistemology.William Talbott - 2006 - Stanford Encyclopedia of Philosophy.
    ‘Bayesian epistemology’ became an epistemological movement in the 20th century, though its two main features can be traced back to the eponymous Reverend Thomas Bayes (c. 1701-61). Those two features are: (1) the introduction of a formal apparatus for inductive logic; (2) the introduction of a pragmatic self-defeat test (as illustrated by Dutch Book Arguments) for epistemic rationality as a way of extending the justification of the laws of deductive logic to include a justification for the laws of inductive logic. (...)
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  • (1 other version)Logical foundations of probability.Rudolf Carnap - 1950 - Chicago]: Chicago University of Chicago Press.
    APA PsycNET abstract: This is the first volume of a two-volume work on Probability and Induction. Because the writer holds that probability logic is identical with inductive logic, this work is devoted to philosophical problems concerning the nature of probability and inductive reasoning. The author rejects a statistical frequency basis for probability in favor of a logical relation between two statements or propositions. Probability "is the degree of confirmation of a hypothesis (or conclusion) on the basis of some given evidence (...)
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  • (2 other versions)Studies in Inductive Logic and Probability.Rudolf Carnap & Richard C. Jeffrey (eds.) - 1971 - University of California Press.
    A basic system of inductive logic; An axiomatic foundation for the logic of inductive generalization; A survey of inductive systems; On the condition of partial exchangeability; Representation theorems of the de finetti type; De finetti's generalizations of excahngeability; The structure of probabilities defined on first-order languages; A subjectivit's guide to objective chance.
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  • (1 other version)Bayes or Bust?: A Critical Examination of Bayesian Confirmation Theory.John Earman - 1992 - Bradford.
    There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes's original paper to contemporary formal learning theory. (...)
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  • Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.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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  • A subjectivist’s guide to objective chance.David K. Lewis - 2010 - In Antony Eagle (ed.), Philosophy of Probability: Contemporary Readings. New York: Routledge. pp. 263-293.
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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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  • A logic for default reasoning.Ray Reiter - 1980 - Artificial Intelligence 13 (1-2):81-137.
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  • Scientific reasoning: the Bayesian approach.Peter Urbach & Colin Howson - 1993 - Chicago: Open Court. Edited by Peter Urbach.
    Scientific reasoning is—and ought to be—conducted in accordance with the axioms of probability. This Bayesian view—so called because of the central role it accords to a theorem first proved by Thomas Bayes in the late eighteenth ...
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  • (1 other version)Interpretations of probability.Alan Hájek - 2007 - Stanford Encyclopedia of Philosophy.
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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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  • (2 other versions)Generics.Sarah-Jane Leslie - forthcoming - Routledge Encyclopedia of Philosophy.
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  • Generics and the structure of the mind.Sarah-Jane Leslie - 2007 - Philosophical Perspectives 21 (1):375–403.
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  • Degree-of-belief and degree-of-support: Why bayesians need both notions.James Hawthorne - 2005 - Mind 114 (454):277-320.
    I argue that Bayesians need two distinct notions of probability. We need the usual degree-of-belief notion that is central to the Bayesian account of rational decision. But Bayesians also need a separate notion of probability that represents the degree to which evidence supports hypotheses. Although degree-of-belief is well suited to the theory of rational decision, Bayesians have tried to apply it to the realm of hypothesis confirmation as well. This double duty leads to the problem of old evidence, a problem (...)
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  • Probabilities of conditionals and conditional probabilities.David Lewis - 1976 - Philosophical Review 85 (3):297-315.
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  • (1 other version)A nonpragmatic vindication of probabilism.James M. Joyce - 1998 - Philosophy of Science 65 (4):575-603.
    The pragmatic character of the Dutch book argument makes it unsuitable as an "epistemic" justification for the fundamental probabilist dogma that rational partial beliefs must conform to the axioms of probability. To secure an appropriately epistemic justification for this conclusion, one must explain what it means for a system of partial beliefs to accurately represent the state of the world, and then show that partial beliefs that violate the laws of probability are invariably less accurate than they could be otherwise. (...)
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  • (1 other version)The Logic of Conditionals.Ernest Adams, Ernest W. Adams, Jaakko Hintikka & Patrick Suppes - 1965 - Journal of Symbolic Logic 39 (3):609-611.
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  • How to improve Bayesian reasoning without instruction: Frequency formats.Gerd Gigerenzer & Ulrich Hoffrage - 1995 - Psychological Review 102 (4):684-704.
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  • (1 other version)Vision as Bayesian inference: analysis by synthesis?Alan Yuille & Daniel Kersten - 2006 - Trends in Cognitive Sciences 10 (7):301-308.
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  • In Defence of Objective Bayesianism.Jon Williamson - 2010 - Oxford University Press.
    Objective Bayesianism is a methodological theory that is currently applied in statistics, philosophy, artificial intelligence, physics and other sciences. This book develops the formal and philosophical foundations of the theory, at a level accessible to a graduate student with some familiarity with mathematical notation.
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  • Vision.David Marr - 1982 - W. H. Freeman.
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  • Précis of bayesian rationality: The probabilistic approach to human reasoning.Mike Oaksford & Nick Chater - 2009 - Behavioral and Brain Sciences 32 (1):69-84.
    According to Aristotle, humans are the rational animal. The borderline between rationality and irrationality is fundamental to many aspects of human life including the law, mental health, and language interpretation. But what is it to be rational? One answer, deeply embedded in the Western intellectual tradition since ancient Greece, is that rationality concerns reasoning according to the rules of logic – the formal theory that specifies the inferential connections that hold with certainty between propositions. Piaget viewed logical reasoning as defining (...)
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  • (1 other version)The logic of conditionals.Ernest Adams - 1965 - Inquiry: An Interdisciplinary Journal of Philosophy 8 (1-4):166 – 197.
    The standard use of the propositional calculus ('P.C.?) in analyzing the validity of inferences involving conditionals leads to fallacies, and the problem is to determine where P.C. may be ?safely? used. An alternative analysis of criteria of reasonableness of inferences in terms of conditions of justification rather than truth of statements is proposed. It is argued, under certain restrictions, that P. C. may be safely used, except in inferences whose conclusions are conditionals whose antecedents are incompatible with the premises in (...)
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  • Generics and the ways of normality.Bernhard Nickel - 2008 - Linguistics and Philosophy 31 (6):629-648.
    I contrast two approaches to the interpretation of generics such as ‘ravens are black:’ majority-based views, on which they are about what is the case most of the time, and inquiry-based views, on which they are about a feature we focus on in inquiry. I argue that majority-based views face far more systematic counterexamples than has previously been supposed. They cannot account for generics about kinds with multiple characteristic properties, such as ‘elephants live in Africa and Asia.’ I then go (...)
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  • Bayesian Epistemology.Luc Bovens & Stephan Hartmann - 2003 - Oxford: Oxford University Press. Edited by Stephan Hartmann.
    Probabilistic models have much to offer to philosophy. We continually receive information from a variety of sources: from our senses, from witnesses, from scientific instruments. When considering whether we should believe this information, we assess whether the sources are independent, how reliable they are, and how plausible and coherent the information is. Bovens and Hartmann provide a systematic Bayesian account of these features of reasoning. Simple Bayesian Networks allow us to model alternative assumptions about the nature of the information sources. (...)
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  • Conditional probabilities and compounds of conditionals.Vann McGee - 1989 - Philosophical Review 98 (4):485-541.
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  • (2 other versions)Generics: Cognition and acquisition.Sarah-Jane Leslie - 2008 - Philosophical Review 117 (1):1-47.
    Ducks lay eggs' is a true sentence, and `ducks are female' is a false one. Similarly, `mosquitoes carry the West Nile virus' is obviously true, whereas `mosquitoes don't carry the West Nile virus' is patently false. This is so despite the egg-laying ducks' being a subset of the female ones and despite the number of mosquitoes that don't carry the virus being ninety-nine times the number that do. Puzzling facts such as these have made generic sentences defy adequate semantic treatment. (...)
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  • (2 other versions)A Philosophical Guide to Conditionals.Jonathan Bennett - 2003 - Bulletin of Symbolic Logic 10 (4):565-570.
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  • A Philosophical Guide to Conditionals.W. G. Lycan - 2005 - Mind 114 (453):116-119.
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  • (1 other version)Bayes or Bust?: A Critical Examination of Bayesian Confirmation Theory. [REVIEW]Alan Hajek & Brian Skyrms - 2000 - Philosophical and Phenomenological Research 60 (3):707-711.
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  • (1 other version)Arguments For—Or Against—Probabilism?Alan Hájek - 2009 - In Franz Huber & Christoph Schmidt-Petri (eds.), Degrees of belief. London: Springer. pp. 229--251.
    Four important arguments for probabilism—the Dutch Book, representation theorem, calibration, and gradational accuracy arguments—have a strikingly similar structure. Each begins with a mathematical theorem, a conditional with an existentially quantified consequent, of the general form: if your credences are not probabilities, then there is a way in which your rationality is impugned. Each argument concludes that rationality requires your credences to be probabilities. I contend that each argument is invalid as formulated. In each case there is a mirror-image theorem and (...)
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  • Conditional reasoning with inducements and advice.J. Evans - 1998 - Cognition 69 (1):B11-B16.
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  • The Probabilistic Mind: Prospects for Bayesian Cognitive Science.Nick Chater & Mike Oaksford (eds.) - 2008 - Oxford University Press.
    'The Probabilistic Mind' is a follow-up to the influential and highly cited 'Rational Models of Cognition'. It brings together developments in understanding how, and how far, high-level cognitive processes can be understood in rational terms, and particularly using probabilistic Bayesian methods.
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  • Bayesian confirmation theory: Inductive logic, or mere inductive framework?Michael Strevens - 2004 - Synthese 141 (3):365 - 379.
    Does the Bayesian theory of confirmation put real constraints on our inductive behavior? Or is it just a framework for systematizing whatever kind of inductive behavior we prefer? Colin Howson (Hume's Problem) has recently championed the second view. I argue that he is wrong, in that the Bayesian apparatus as it is usually deployed does constrain our judgments of inductive import, but also that he is right, in that the source of Bayesianism's inductive prescriptions is not the Bayesian machinery itself, (...)
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  • (1 other version)Letting Structure Emerge: Connectionist and Dynamical Systems Approaches to Cognition.Linda B. Smith James L. McClelland, Matthew M. Botvinick, David C. Noelle, David C. Plaut, Timothy T. Rogers, Mark S. Seidenberg - 2010 - Trends in Cognitive Sciences 14 (8):348.
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  • Verisimilitude and Belief Change for Conjunctive Theories.Gustavo Cevolani, Vincenzo Crupi & Roberto Festa - 2011 - Erkenntnis 75 (2):183-202.
    Theory change is a central concern in contemporary epistemology and philosophy of science. In this paper, we investigate the relationships between two ongoing research programs providing formal treatments of theory change: the (post-Popperian) approach to verisimilitude and the AGM theory of belief change. We show that appropriately construed accounts emerging from those two lines of epistemological research do yield convergences relative to a specified kind of theories, here labeled “conjunctive”. In this domain, a set of plausible conditions are identified which (...)
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  • What is 'normal'? An evolution-theoretic foundation for normic laws and their relation to statistical normality.Gerhard Schurz - 2001 - Philosophy of Science 68 (4):476-497.
    Normic laws have the form "if A, then normally B." They are omnipresent in everyday life and non-physical 'life' sciences such as biology, psychology, social sciences, and humanities. They differ significantly from ceteris-paribus laws in physics. While several authors have doubted that normic laws are genuine laws at all, others have argued that normic laws express a certain kind of prototypical normality which is independent of statistical majority. This paper presents a foundation for normic laws which is based on generalized (...)
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  • (1 other version)Theory-based Bayesian models of inductive learning and reasoning.Joshua B. Tenenbaum, Thomas L. Griffiths & Charles Kemp - 2006 - Trends in Cognitive Sciences 10 (7):309-318.
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  • (1 other version)Logical Foundations of Probability (2nd edition).Rudolf Carnap - 1962 - Chicago: Chicago University Press.
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  • Prototypes and their Composition from an Evolutionary Point of View.G. Schurz - 2012 - In Markus Werning, Wolfram Hinzen & Edouard Machery (eds.), The Oxford Handbook of Compositionality. Oxford University Press. pp. 530--553.
    The foregoing considerations support the conjecture that prototypes are semi-compositional in the sense that there exist unboundedly many combinations of nouns with non-exceptional adjectives, which satisfy the rule default-to-prototype and hence are compositional. Presumably there also exist unboundedly many combinations of nouns with exceptional adjectives, which violate DP and hence are non-compositional. An analysis of the connection between productivity and compositionality has been suggested by Robbins. He argues that, for the explanation of productivity, one need not assume that conceptual meanings (...)
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