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  1. (1 other version)Challenges to Bayesian Confirmation Theory.John D. Norton - 2011 - In Prasanta S. Bandyopadhyay & Malcolm Forster (eds.), Handbook of the Philosophy of Science, Vol. 7: Philosophy of Statistics. Elsevier B.V.. pp. 391-440.
    Proponents of Bayesian confirmation theory believe that they have the solution to a significant, recalcitrant problem in philosophy of science. It is the identification of the logic that governs evidence and its inductive bearing in science. That is the logic that lets us say that our catalog of planetary observations strongly confirms Copernicus’ heliocentric hypothesis; or that the fossil record is good evidence for the theory of evolution; or that the 3oK cosmic background radiation supports big bang cosmology. The definitive (...)
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  • The normative representation of quantified beliefs by belief functions.Philippe Smets - 1997 - Artificial Intelligence 92 (1--2):229--242.
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  • Cooperation, psychological game theory, and limitations of rationality in social interaction.Andrew M. Colman - 2003 - Behavioral and Brain Sciences 26 (2):139-153.
    Rational choice theory enjoys unprecedented popularity and influence in the behavioral and social sciences, but it generates intractable problems when applied to socially interactive decisions. In individual decisions, instrumental rationality is defined in terms of expected utility maximization. This becomes problematic in interactive decisions, when individuals have only partial control over the outcomes, because expected utility maximization is undefined in the absence of assumptions about how the other participants will behave. Game theory therefore incorporates not only rationality but also common (...)
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  • Varieties of Bayesianism.Jonathan Weisberg - 2011
    Handbook of the History of Logic, vol. 10, eds. Dov Gabbay, Stephan Hartmann, and John Woods, forthcoming.
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  • Theories of probability.Colin Howson - 1995 - British Journal for the Philosophy of Science 46 (1):1-32.
    My title is intended to recall Terence Fine's excellent survey, Theories of Probability [1973]. I shall consider some developments that have occurred in the intervening years, and try to place some of the theories he discussed in what is now a slightly longer perspective. Completeness is not something one can reasonably hope to achieve in a journal article, and any selection is bound to reflect a view of what is salient. In a subject as prone to dispute as this, there (...)
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  • A logico-geometric comparison of coherence for non-additive uncertainty measures.Esther Anna Corsi, Tommaso Flaminio & Hykel Hosni - 2024 - Annals of Pure and Applied Logic 175 (9):103342.
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  • Bayesian diagnosis in expert systems.Gernot D. Kleiter - 1992 - Artificial Intelligence 54 (1-2):1-32.
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  • Two views of belief: belief as generalized probability and belief as evidence.Joseph Y. Halpern & Ronald Fagin - 1992 - Artificial Intelligence 54 (3):275-317.
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  • The transferable belief model.Philippe Smets & Robert Kennes - 1994 - Artificial Intelligence 66 (2):191-234.
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  • Credal networks.Fabio G. Cozman - 2000 - Artificial Intelligence 120 (2):199-233.
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  • (1 other version)Imprecise Probabilities.Seamus Bradley - 2019 - Stanford Encyclopedia of Philosophy.
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  • Regular updating.Alain Chateauneuf, Thibault Gajdos & Jean-Yves Jaffray - 2011 - Theory and Decision 71 (1):111-128.
    We study the Full Bayesian Updating rule for convex capacities. Following a route suggested by Jaffray (IEEE Transactions on Systems, Man and Cybernetics 22(5):1144–1152, 1992), we define some properties one may want to impose on the updating process, and identify the classes of (convex and strictly positive) capacities that satisfy these properties for the Full Bayesian Updating rule. This allows us to characterize two parametric families of convex capacities: ${(\varepsilon,\delta)}$ -contaminations (which were introduced, in a slightly different form, by Huber (...)
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  • The limitation of Bayesianism.Pei Wang - 2004 - Artificial Intelligence 158 (1):97-106.
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  • Probabilistic Logics and Probabilistic Networks.Rolf Haenni, Jan-Willem Romeijn, Gregory Wheeler & Jon Williamson - 2010 - Dordrecht, Netherland: Synthese Library. Edited by Gregory Wheeler, Rolf Haenni, Jan-Willem Romeijn & and Jon Williamson.
    Additionally, the text shows how to develop computationally feasible methods to mesh with this framework.
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  • Learning and Pooling, Pooling and Learning.Rush T. Stewart & Ignacio Ojea Quintana - 2018 - Erkenntnis 83 (3):1-21.
    We explore which types of probabilistic updating commute with convex IP pooling. Positive results are stated for Bayesian conditionalization, imaging, and a certain parameterization of Jeffrey conditioning. This last observation is obtained with the help of a slight generalization of a characterization of externally Bayesian pooling operators due to Wagner :336–345, 2009). These results strengthen the case that pooling should go by imprecise probabilities since no precise pooling method is as versatile.
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  • Measures of uncertainty in expert systems.Peter Walley - 1996 - Artificial Intelligence 83 (1):1-58.
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  • Bridging psychology and game theory yields interdependence theory.Paul A. M. Van Lange & Marcello Gallucci - 2003 - Behavioral and Brain Sciences 26 (2):177-178.
    This commentary focuses on the parts of psychological game theory dealing with preference, as illustrated by team reasoning, and supports the conclusion that these theoretical notions do not contribute above and beyond existing theory in understanding social interaction. In particular, psychology and games are already bridged by a comprehensive, formal, and inherently psychological theory, interdependence theory (Kelley & Thibaut 1978; Kelley et al. 2003), which has been demonstrated to account for a wide variety of social interaction phenomena.
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  • Introduction.Gregory Wheeler - 2012 - Synthese 186 (2):443-446.
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  • Epistemology and artificial intelligence.Gregory R. Wheeler & Luís Moniz Pereira - 2004 - Journal of Applied Logic 2 (4):469-493.
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  • On the justification of Dempster's rule of combination.Frans Voorbraak - 1991 - Artificial Intelligence 48 (2):171-197.
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  • The vulnerability of the transferable belief model to Dutch books.Paul Snow - 1998 - Artificial Intelligence 105 (1-2):345-354.
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  • A two-level system of knowledge representation based on evidential probability.Henry E. Kyburg - 1991 - Philosophical Studies 64 (1):105 - 114.
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  • Probabilistic Inference and Probabilistic Reasoning. Kyburg - 1990 - Philosophical Topics 18 (2):107-116.
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