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  1. (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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  • (1 other version)Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - New York: Cambridge University Press.
    Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence, business, epidemiology, social science and economics.
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  • The structure of empirical knowledge.Laurence BonJour - 1985 - Cambridge: Harvard University Press.
    1 Knowledge and Justification This book is an investigation of one central problem which arises in the attempt to give a philosophical account of empirical ...
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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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  • (1 other version)An Analysis of Knowledge and Valuation.C. I. Lewis - 1946 - Mind 57 (225):71-85.
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  • (1 other version)Logical Foundations of Probability.Rudolf Carnap - 1950 - Mind 62 (245):86-99.
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  • Probability and the Art of Judgment.Richard C. Jeffrey - 1992 - New York: Cambridge University Press.
    Richard Jeffrey is beyond dispute one of the most distinguished and influential philosophers working in the field of decision theory and the theory of knowledge. His work is distinctive in showing the interplay of epistemological concerns with probability and utility theory. Not only has he made use of standard probabilistic and decision theoretic tools to clarify concepts of evidential support and informed choice, he has also proposed significant modifications of the standard Bayesian position in order that it provide a better (...)
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  • Confirming Power of Observations Metricized for Decisions among Hypotheses.Henry A. Finch - 1960 - Philosophy of Science 27 (3):293-307.
    Experimental observations are often taken in order to assist in making a choice between relevant hypotheses ~H and H. The power of observations in this decision is here metrically defined by information-theoretic concepts and Bayes' theorem. The exact of a new observation to increase or decrease Pr the prior probability that H is true; the power of that observation to modify the total amount of uncertainty involved in the choice between ~H and H: the power of a new observation to (...)
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  • Equivalent testimonies as a touchstone of coherence measures.Mark Siebel & Werner Wolff - 2008 - Synthese 161 (2):167-182.
    Over the past years, a number of probabilistic measures of coherence have been proposed. As shown in the paper, however, many of them do not conform to the intuitition that equivalent testimonies are highly coherent, regardless of their prior probability.
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  • Bayesian confirmation: Paradise regained.R. D. Rosenkrantz - 1994 - British Journal for the Philosophy of Science 45 (2):467-476.
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  • Corroboration and rules of acceptance.Isaac Levi - 1962 - British Journal for the Philosophy of Science 13 (52):307-313.
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  • Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - Tijdschrift Voor Filosofie 64 (1):201-202.
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  • (1 other version)A Treatise on Probability.J. M. Keynes - 1989 - British Journal for the Philosophy of Science 40 (2):219-222.
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  • A probabilistic theory of coherence.Branden Fitelson - 2003 - Analysis 63 (3):194-199.
    Let E be a set of n propositions E1, ..., En. We seek a probabilistic measure C(E) of the ‘degree of coherence’ of E. Intuitively, we want C to be a quantitative, probabilistic generalization of the (deductive) logical coherence of E. So, in particular, we require C to satisfy the following..
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  • (1 other version)Degree of confirmation.Karl R. Popper - 1954 - British Journal for the Philosophy of Science 5 (18):143-149.
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  • In defense of the Popper-Miller argument.Donald Gillies - 1986 - Philosophy of Science 53 (1):110-113.
    In their 1983 article, Popper and Miller present an argument against inductive probability. This argument is criticized by Redhead in his 1985 article. The aim of the present note is to state one form of the Popper-Miller argument, and defend it against Redhead's criticisms.
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  • Measuring coherence.Igor Douven & Wouter Meijs - 2007 - Synthese 156 (3):405 - 425.
    This paper aims to contribute to our understanding of the notion of coherence by explicating in probabilistic terms, step by step, what seem to be our most basic intuitions about that notion, to wit, that coherence is a matter of hanging or fitting together, and that coherence is a matter of degree. A qualitative theory of coherence will serve as a stepping stone to formulate a set of quantitative measures of coherence, each of which seems to capture well the aforementioned (...)
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  • (1 other version)An Analysis of Knowledge and Valuation.C. I. Lewis - 1949 - Review of Metaphysics 2 (7):99-115.
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  • Against coherence: truth, probability, and justification.Erik J. Olsson - 2005 - New York: Oxford University Press.
    It is tempting to think that, if a person's beliefs are coherent, they are also likely to be true. This truth conduciveness claim is the cornerstone of the popular coherence theory of knowledge and justification. Erik Olsson's new book is the most extensive and detailed study of coherence and probable truth to date. Setting new standards of precision and clarity, Olsson argues that the value of coherence has been widely overestimated. Provocative and readable, Against Coherence will make stimulating reading for (...)
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  • (1 other version)Degree of Confirmation.Karl R. Popper - 1955 - Journal of Symbolic Logic 20 (3):304-305.
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  • Is coherence truth conducive?Tomoji Shogenji - 1999 - Analysis 59 (4):338-345.
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  • Reliability conducive measures of coherence.Erik J. Olsson & Stefan Schubert - 2007 - Synthese 157 (3):297-308.
    A measure of coherence is said to be truth conducive if and only if a higher degree of coherence (as measured) results in a higher likelihood of truth. Recent impossibility results strongly indicate that there are no (non-trivial) probabilistic coherence measures that are truth conducive. Indeed, this holds even if truth conduciveness is understood in a weak ceteris paribus sense (Bovens & Hartmann, 2003, Bayesian epistemology. New York, Oxford: Oxford University Press; Olsson, 2005, Against coherence: Truth probability and justification. Oxford: (...)
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  • An Analysis of Knowledge and Valuation.Clarence Irving Lewis - 1946 - La Salle, IL, USA: Open Court.
    We are republishing these classic works in affordable, high quality, modern editions, using the original text and artwork.
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  • Coherence as a heuristic.Staffan Angere - 2008 - Mind 117 (465):1-26.
    The impossibility results of Bovens and Hartmann (2003) and Olsson (2005) call into question the strength of the connection between coherence and truth. As part of the inquiry into this alleged link, I define a notion of degree of truth-conduciveness, relevant for measuring the usefulness of coherence measures as rules-of-thumb for assigning probabilities in situations of partial knowledge. I use the concept to compare the viability of some of the measures of coherence that have been suggested so far under different (...)
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  • Wittgensteinian bayesianism.Paul Horwich - 1993 - Midwest Studies in Philosophy 18 (1):62-75.
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  • Log[p(h/eb)/p(h/b)] is the one true measure of confirmation.Peter Milne - 1996 - Philosophy of Science 63 (1):21-26.
    Plausibly, when we adopt a probabilistic standpoint any measure Cb of the degree to which evidence e confirms hypothesis h relative to background knowledge b should meet these five desiderata: Cb > 0 when P > P < 0 when P < P; Cb = 0 when P = P. Cb is some function of the values P and P assume on the at most sixteen truth-functional combinations of e and h. If P < P and P = P then (...)
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  • Coherentism, reliability and bayesian networks.Luc Bovens & Erik J. Olsson - 2000 - Mind 109 (436):685-719.
    The coherentist theory of justification provides a response to the sceptical challenge: even though the independent processes by which we gather information about the world may be of dubious quality, the internal coherence of the information provides the justification for our empirical beliefs. This central canon of the coherence theory of justification is tested within the framework of Bayesian networks, which is a theory of probabilistic reasoning in artificial intelligence. We interpret the independence of the information gathering processes (IGPs) in (...)
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  • Measuring Degrees of Confirmation.George N. Schlesinger - 1995 - Analysis 55 (3):208 - 212.
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  • Believing more, risking less: On coherence, truth and non-trivial extensions.Luc Bovens & Erik J. Olsson - 2002 - Erkenntnis 57 (2):137 - 150.
    If you believe more things you thereby run a greater risk of being in error than if you believe fewer things. From the point of view of avoiding error, it is best not to believe anything at all, or to have very uncommitted beliefs. But considering the fact that we all in fact do entertain many specific beliefs, this recommendation is obviously in flagrant dissonance with our actual epistemic practice. Let us call the problem raised by this apparent conflict the (...)
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  • (1 other version)A treatise on probability.J. Keynes - 1924 - Revue de Métaphysique et de Morale 31 (1):11-12.
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  • Evidentiary Value: Philosophical, Judicial and Psychological Aspects of a Theory. [REVIEW]B. Hansson - 1984 - British Journal for the Philosophy of Science 35 (3):293-296.
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