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  1.  18
    Henry Kyburg (1974). The Logical Foundations of Statistical Inference. Reidel.
    At least one of these conceptions of probability underlies any theory of statistical inference (or, to use Neyman's phrase, 'inductive behavior'). ...
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  2.  28
    Henry E. Kyburg Jr (1961). Probability and the Logic of Rational Belief. Wesleyan University Press.
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  3.  27
    Henry E. Kyburg Jr (2010). Subjective Probability : Criticisms, Reflections and Problems. [REVIEW] In Antony Eagle (ed.), Journal of Philosophical Logic. Routledge 157 - 180.
  4.  6
    Henry Ely Kyburg (1961). Probability and the Logic of Rational Belief. Middletown, Conn.,Wesleyan University Press.
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  5. Henry Ely Kyburg & Choh Man Teng (2001). Uncertain Inference. Monograph Collection (Matt - Pseudo).
    Coping with uncertainty is a necessary part of ordinary life and is crucial to an understanding of how the mind works. For example, it is a vital element in developing artificial intelligence that will not be undermined by its own rigidities. There have been many approaches to the problem of uncertain inference, ranging from probability to inductive logic to nonmonotonic logic. Thisbook seeks to provide a clear exposition of these approaches within a unified framework. The principal market for the book (...)
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  6.  12
    Henry E. Kyburg (1983). Rational Belief. Behavioral and Brain Sciences 6 (2):231.
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  7.  14
    Henry E. Kyburg (ed.) (1984). Theory and Measurement. Cambridge University Press.
    Measurement is fundamental to all the sciences, the behavioural and social as well as the physical and in the latter its results provide our paradigms of 'objective fact'. But the basis and justification of measurement is not well understood and is often simply taken for granted. Henry Kyburg Jr proposes here an original, carefully worked out theory of the foundations of measurement, to show how quantities can be defined, why certain mathematical structures are appropriate to them and what meaning attaches (...)
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  8.  53
    Gregory Wheeler, Henry E. Kyburg & Choh Man Teng (2007). Conditionals and Consequences. Journal of Applied Logic 5 (4):638-650.
    We examine the notion of conditionals and the role of conditionals in inductive logics and arguments. We identify three mistakes commonly made in the study of, or motivation for, non-classical logics. A nonmonotonic consequence relation based on evidential probability is formulated. With respect to this acceptance relation some rules of inference of System P are unsound, and we propose refinements that hold in our framework.
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  9. Henry E. Kyburg Jr (1981). Leeds' Infernal Machine. Philosophy of Science 48 (1):92-94.
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  10. Henry E. Kyburg Jr (1970). ``Conjunctivitis&Quot. In Marshall Swain (ed.), Induction, Acceptance, and Rational Belief. Dordrecht: D. Reidel 55-82.
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  11.  7
    Henry E. Kyburg (1980). Acts and Conditional Probabilities. Theory and Decision 12 (2):149-171.
  12.  37
    Henry E. Kyburg Jr (1997). The Rule of Adjunction and Reasonable Inference. Journal of Philosophy 94 (3):109-125.
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  13. Henry Ely Kyburg (ed.) (1980). Studies in Subjective Probability. Krieger.
     
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  14.  24
    Henry E. Kyburg Jr (1977). Randomness and the Right Reference Class. Journal of Philosophy 74 (9):501-521.
  15.  5
    Henry E. Kyburg (1981). Intuition, Competence, and Performance. Behavioral and Brain Sciences 4 (3):341.
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  16. William L. Harper & Henry E. Kyburg (1968). The Jones Case. British Journal for the Philosophy of Science 19 (3):247-251.
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  17. Henry Ely Kyburg (1970). Probability and Inductive Logic. [New York]Macmillan.
     
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  18. Henry E. Kyburg Jr (1980). Conditionalization. Journal of Philosophy 77 (2):98-114.
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  19.  28
    Henry E. Kyburg Jr (1983). The Reference Class. Philosophy of Science 50 (3):374-397.
    The system presented by the author in The Logical Foundations of Statistical Inference (Kyburg 1974) suffered from certain technical difficulties, and from a major practical difficulty; it was hard to be sure, in discussing examples and applications, when you had got hold of the right reference class. The present paper, concerned mainly with the characterization of randomness, resolves the technical difficulties and provides a well structured framework for the choice of a reference class. The definition of randomness that leads to (...)
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  20.  7
    Henry E. Kyburg (1988). Full Belief. Theory and Decision 25 (2):137.
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  21.  10
    Henry Kyburg (1983). Recent Work in Inductive Logic. In Kenneth G. Lucey & Tibor R. Machan (eds.), American Philosophical Quarterly. Rowman & Allanheld 87--150.
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  22. Henry E. Kyburg (1976). Chance. Journal of Philosophical Logic 5 (3):355-393.
  23.  40
    Henry E. Kyburg Jr (1997). Quantities, Magnitudes, and Numbers. Philosophy of Science 64 (3):377-410.
    Quantities are naturally viewed as functions, whose arguments may be construed as situations, events, objects, etc. We explore the question of the range of these functions: should it be construed as the real numbers (or some subset thereof)? This is Carnap's view. It has attractive features, specifically, what Carnap views as ontological economy. Or should the range of a quantity be a set of magnitudes? This may have been Helmholtz's view, and it, too, has attractive features. It reveals the close (...)
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  24.  16
    Henry E. Kyburg Jr (1965). Salmon's Paper. Philosophy of Science 32 (2):147-151.
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  25.  41
    Henry E. Kyburg Jr (1981). Principle Investigation. Journal of Philosophy 78 (12):772-778.
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  26.  20
    Henry E. Kyburg (1988). Review. [REVIEW] Synthese 76 (1):179-182.
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  27.  16
    Henry E. Kyburg (2002). Don't Take Unnecessary Chances! Synthese 132 (1-2):9-26.
    The dominant argument for the introduction of propensities or chances as an interpretation of probability depends on the difficulty of accounting for single case probabilities. We argue that in almost all cases, the``single case'' application of probability can be accounted for otherwise. ``Propensities'' are needed only intheoretical contexts, and even there applications of probability need only depend on propensities indirectly.
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  28.  67
    William L. Harper & Henry E. Kyburg (1968). Discussions: The Jones Case. British Journal for the Philosophy of Science 19 (3):247-251.
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  29.  5
    Henry E. Kyburg (1962). Reviewed Work: Prediction and Optimal Decision: Philosophical Issues of a Science of Values by C. West Churchman. [REVIEW] Journal of Philosophy 59 (20):549-554.
  30.  22
    Henry E. Kyburg (1979). Tyche and Athena. Synthese 40 (3):415 - 438.
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  31.  35
    Henry E. Kyburg (1963). Probability and Randomness. Theoria 29 (1):27-55.
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  32.  5
    Henry E. Kyburg (1968). Bets and Beliefs. American Philosophical Quarterly 5 (1):54-63.
  33. Henry Ely Kyburg (1968). Philosophy of Science. New York, Macmillan.
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  34.  61
    Henry E. Kyburg Jr (1956). The Justification of Induction. Journal of Philosophy 53 (12):394-400.
  35.  17
    Henry E. Kyburg (1977). Decisions, Conclusions, and Utilities. Synthese 36 (1):87-96.
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  36.  9
    Henry E. Kyburg (1991). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference by Judea Pearl. Journal of Philosophy 88 (8):434-437.
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  37.  12
    Henry E. Kyburg (1971). Reviews. [REVIEW] Synthese 22 (3-4):482-493.
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  38.  6
    Mazhar Hasan & Henry E. Kyburg Jr (2011). Worlds‐Antiworlds; Antimatter in Cosmology, Hannes Alfven. World Futures 11 (sup1):1-10.
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  39.  10
    Henry E. Kyburg Jr (1987). The Hobgoblin. The Monist 70 (2):141-151.
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  40.  29
    Henry E. Kyburg (1992). Getting Fancy with Probability. Synthese 90 (2):189-203.
    There are a number of reasons for being interested in uncertainty, and there are also a number of uncertainty formalisms. These formalisms are not unrelated. It is argued that they can all be reflected as special cases of the approach of taking probabilities to be determined by sets of probability functions defined on an algebra of statements. Thus, interval probabilities should be construed as maximum and minimum probabilities within a set of distributions, Glenn Shafer's belief functions should be construed as (...)
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  41. E. Kyburg, Henry (1987). Bayesian and Non-Bayesian Evidential Updating. Artificial Intelligence 31:271--294.
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  42.  10
    Henry E. Kyburg Jr (1987). Rational Decision and Causality. International Studies in Philosophy 19 (1):72-74.
  43.  25
    Henry E. Kyburg Jr (2001). Probability as a Guide in Life. The Monist 84 (2):135-152.
    Bishop Butler, [Butler, 1736], said that probability was the very guide of life. But what interpretations of probability can serve this function? It isn’t hard to see that empirical (frequency) views won’t do, and many recent writers-for example John Earman, who has said that Bayesianism is “the only game in town”-have been persuaded by various dutch book arguments that only subjective probability will perform the function required. We will defend the thesis that probability construed in this way offers very little (...)
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  44.  44
    Henry E. Kyburg Jr (2006). Belief, Evidence, and Conditioning. Philosophy of Science 73 (1):42-65.
    Since Ramsey, much discussion of the relation between probability and belief has taken for granted that there are degrees of belief, i.e., that there is a real-valued function, B, that characterizes the degree of belief that an agent has in each statement of his language. It is then supposed that B is a probability. It is then often supposed that as the agent accumulates evidence, this function should be updated by conditioning: BE(·) should be B(·E)/B(E). Probability is also important in (...)
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  45.  21
    Stephen Leeds, John L. Pollock & Henry E. Kyburg (1985). A Problem About Frequencies in Direct Inference. Philosophical Studies 48 (1):137 - 140.
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  46.  10
    Henry E. Kyburg & David A. Nelson (1994). Discussion Reviews. Minds and Machines 4 (1):81-101.
  47.  12
    Henry E. Kyburg (1991). A Two-Level System of Knowledge Representation Based on Evidential Probability. Philosophical Studies 64 (1):105 - 114.
  48.  27
    Henry E. Kyburg Jr (2001). Real Logic is Nonmonotonic. Minds and Machines 11 (4):577-595.
    Charles Morgan has argued that nonmonotonic logic is ``impossible''. We show here that those arguments are mistaken, and that Morgan's preferred alternative, the representation of nonmonotonic reasoning by ``presuppositions'' fails to provide a framework in which nonmonotonic reasoning can be constructively criticised. We argue that an inductive logic, based on probabilistic acceptance, offers more than Morgan's approach through presuppositions.
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  49.  33
    Henry E. Kyburg (1997). Thinking About Reasoning About Knowledge. Minds and Machines 7 (1):103-112.
  50.  2
    Henry E. Kyburg Jr (1996). Dennett's Beer. In K. M. Ford & Z. W. Pylyshyn (eds.), The Robot's Dilemma Revisited: The Frame Problem in Artificial Intelligence. Ablex
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