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  1. P. Alexander (1959). HARROD, R. F. -Foundations of Inductive Logic. [REVIEW] Mind 68:108.
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  2. Alexander Bain (1874). Logic Deductive and Inductive. D. Appleton.
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  3. W. Ballantine (1896). Inductive Logic. Philosophical Review 5:332.
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  4. Prasanta S. Bandyopadhyay & Malcolm Forster (eds.) (forthcoming). Philosophy of Statistics, Handbook of the Philosophy of Science, Volume 7. Elsevier.
  5. Y. Bar-Hillel (1968). Bunge and Watkins on Inductive Logic. In Imre Lakatos (ed.), The Problem of Inductive Logic. Amsterdam, North Holland Pub. Co.. 282--85.
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  6. Yehoshua Bar-Hillel (1968). Inductive Logic as" the" Guide of Life'. In Imre Lakatos (ed.), The Problem of Inductive Logic. Amsterdam, North Holland Pub. Co.. 66--69.
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  7. Yehoshua Bar-Hillel (1964). On an Alleged Contradiction in Carnap's Theory of Inductive Logic. Mind 73 (290):265-267.
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  8. Yehoshua Bar-Hillel (1953). A Note on Comparative Inductive Logic. British Journal for the Philosophy of Science 3 (12):308-310.
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  9. Yann Benétreau-Dupin (forthcoming). The Bayesian Who Knew Too Much. Synthese:1-16.
    In several papers, John Norton has argued that Bayesianism cannot handle ignorance adequately due to its inability to distinguish between neutral and disconfirming evidence. He argued that this inability sows confusion in, e.g., anthropic reasoning in cosmology or the Doomsday argument, by allowing one to draw unwarranted conclusions from a lack of knowledge. Norton has suggested criteria for a candidate for representation of neutral support. Imprecise credences (families of credal probability functions) constitute a Bayesian-friendly framework that allows us to avoid (...)
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  10. Johan Van Benthem (2011). Logic in a Social Setting. Episteme 8 (3):227-247.
    Taking Backward Induction as its running example, this paper explores avenues for a logic of information-driven social action. We use recent results on limit phenomena in knowledge updating and belief revision, procedural rationality, and a ‘Theory of Play’ analyzing how games are played by different agents.
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  11. Ken Binmore (2011). Interpreting Knowledge in the Backward Induction Problem. Episteme 8 (3):248-261.
    Robert Aumann argues that common knowledge of rationality implies backward induction in finite games of perfect information. I have argued that it does not. A literature now exists in which various formal arguments are offered in support of both positions. This paper argues that Aumann's claim can be justified if knowledge is suitably reinterpreted.
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  12. Richard J. Blackwell (1979). "Studies in Inductive Probability and Rational Expectation," by Theo A. F. Kuipers. Modern Schoolman 56 (4):386-387.
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  13. S. Butterfield (1983). "Applications of Inductive Logic", Edited by L. J. Cohen and M. B. Hesse. [REVIEW] Mind 92:145.
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  14. R. Carnap & R. Jeffrey (eds.) (1971). Studies in Inductive Logic and Probability. University of California Press.
    Introduction Much delayed, here is the second, final volume of Studies in Inductive Logic and Probability. Carnap projected the series ca. as a ...
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  15. Rudolf Carnap (1996). The Aim of Inductive Logic. In Sahotra Sarkar (ed.), Journal of Symbolic Logic. Garland Pub. Co.. 3--259.
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  16. Rudolf Carnap (1980). A Basic System of Inductive Logic, Part II. In Richard C. Jeffrey (ed.), Studies in Inductive Logic and Probability. Berkeley: University of California Press. 2--7.
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  17. Rudolf Carnap (1963). Variety, Analogy, and Periodicity in Inductive Logic. Philosophy of Science 30 (3):222-227.
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  18. Rudolf Carnap (1951). The Nature and Application of Inductive Logic. Chicago, University of Chicago Press.
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  19. Rudolf Carnap (1951). The Problem of Relations in Inductive Logic. Philosophical Studies 2 (5):75 - 80.
  20. Rudolf Carnap (1947). On the Application of Inductive Logic. Philosophy and Phenomenological Research 8 (1):133-148.
  21. Rudolf Carnap (1945). On Inductive Logic. Philosophy of Science 12 (2):72-97.
  22. Rudolf Carnap & Richard C. Jeffrey (1974). Studies in Inductive Logic and Probability. Volume I. Philosophy and Phenomenological Research 35 (1):128-129.
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  23. Rudolf Carnap & Richard C. Jeffrey (1972). Book Review:Studies in Inductive Logic and Probability Rudolf Carnap, Richard C. Jeffrey. [REVIEW] Philosophy of Science 39 (4):549-.
  24. B. Carr (1974). PIETARINEN, J. "Lawllikeness, Analogy, and Inductive Logic". [REVIEW] Mind 83:625.
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  25. C. West Churchman (1946). Carnap's "on Inductive Logic". Philosophy of Science 13 (4):339-342.
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  26. L. J. Cohen & M. B. Hesse (1983). Applications of Inductive Logic. Mind 92 (365):145-147.
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  27. L. J. Cohen & Mary Hesse (eds.) (1983). Aspects of Inductive Logic. Oxford Up.
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  28. L. Jonathan Cohen (1973). A Note on Inductive Logic. Journal of Philosophy 70 (2):27-40.
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  29. L. Jonathan Cohen & Mary B. Hesse (eds.) (1980). Applications of Inductive Logic: Proceedings of a Conference at the Queen's College, Oxford 21-24, August 1978. Oxford University Press.
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  30. N. C. A. Da Costa (1987). Outlines of a System of Inductive Logic'. Theoria 7:3-13.
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  31. Wilhelm K. Essler (1986). How to Apply and Justify Inductive Logic. Erkenntnis 24 (1):47 - 55.
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  32. S. M. F. (1967). Choice and Chance: An Introduction to Inductive Logic. [REVIEW] Review of Metaphysics 20 (4):733-733.
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  33. Roberto Festa (1999). Bayesian Confirmation. In M. C. Galavotti & A. Pagnini (eds.), Experience, Reality, and Scientific Explanation. Kluwer. 55–87.
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  34. Branden Fitelson (2003). Review of I. Hacking, An Introduction to Probability and Inductive Logic. [REVIEW] Bulletin of Symbolic Logic 9 (4):5006-5008.
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  35. Thomas Fowler (1893). Logic Deductive and Inductive. At the Clarendon Press.
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  36. Thomas Fowler (1872). The Elements of Inductive Logic Designed Mainly for the Use of Students in the Universities. At the Clarendon Press.
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  37. Thomas Fowler (1870). The Elements of Inductive Logic.
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  38. George Stuart Fullerton (1908). Enn's Principles of Empirical or Inductive Logic. [REVIEW] Journal of Philosophy 5 (11):297.
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  39. G. G. G. G. (1908). VENN, J. -Principles of Empirical or Inductive Logic. [REVIEW] Mind 17:280.
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  40. Ian Hacking (2001). An Introduction to Probability and Inductive Logic. Cambridge University Press.
    This is an introductory textbook on probability and induction written by one of the world's foremost philosophers of science. The book has been designed to offer maximal accessibility to the widest range of students (not only those majoring in philosophy) and assumes no formal training in elementary symbolic logic. It offers a comprehensive course covering all basic definitions of induction and probability, and considers such topics as decision theory, Bayesianism, frequency ideas, and the philosophical problem of induction. The key features (...)
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  41. Ian Hacking (1971). The Leibniz-Carnap Program for Inductive Logic. Journal of Philosophy 68 (19):597-610.
  42. Ian Hacking (1969). Linguistically Invariant Inductive Logic. Synthese 20 (1):25 - 47.
    Carnap's early system of inductive logic make degrees of confirmation depend on the languages in which they are expressed. They are sensitive to which predicates are, in the language, taken as primitive. Hence they fail to be ‘linguistically invariant’. His later systems, in which prior probabilities are assigned to elements of a model rather than sentences of a language, are sensitive to which properties in the model are called primitive. Critics have often protested against these features of his work. This (...)
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  43. D. W. Hamlyn (1958). Foundations of Inductive Logic. By R. F. Harrod. (London: Macmillan. 1956. Pp. Xviii + 290. Price 24s.). Philosophy 33 (127):369-.
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  44. Roy Forbes Harrod (1974/1957). Foundations of Inductive Logic. Macmillan.
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  45. James Hawthorne (2011). Bayesian Confirmation Theory. In S. French & J. Saatsi (eds.), Continuum Companion to the Philosophy of Science. Continuum Press.
    Scientifi c theories and hypotheses make claims that go well beyond what we can immediately observe. How can we come to know whether such claims are true? The obvious approach is to see what a hypothesis says about the observationally accessible parts of the world. If it gets that wrong, then it must be false; if it gets that right, then it may have some claim to being true. Any sensible a empt to construct a logic that captures how we (...)
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  46. James Hawthorne (2011). Confirmation Theory. In Prasanta S. Bandyopadhyay & Malcolm Forster (eds.), Philosophy of Statistics, Handbook of the Philosophy of Science, Volume 7. Elsevier.
    Confirmation theory is the study of the logic by which scientific hypotheses may be confirmed or disconfirmed, or even refuted by evidence. A specific theory of confirmation is a proposal for such a logic. Presumably the epistemic evaluation of scientific hypotheses should largely depend on their empirical content – on what they say the evidentially accessible parts of the world are like, and on the extent to which they turn out to be right about that. Thus, all theories of confirmation (...)
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  47. James Hawthorne, Inductive Logic. The Stanford Encyclopedia of Philosophy.
    Sections 1 through 3 present all of the main ideas behind the probabilistic logic of evidential support. For most readers these three sections will suffice to provide an adequate understanding of the subject. Those readers who want to know more about how the logic applies when the implications of hypotheses about evidence claims (called likelihoods) are vague or imprecise may, after reading sections 1-3, skip to section 6. Sections 4 and 5 are for the more advanced reader who wants a (...)
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  48. James Hawthorne (1994). On the Nature of Bayesian Convergence. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1994:241 - 249.
    The objectivity of Bayesian induction relies on the ability of evidence to produce a convergence to agreement among agents who initially disagree about the plausibilities of hypotheses. I will describe three sorts of Bayesian convergence. The first reduces the objectivity of inductions about simple "occurrent events" to the objectivity of posterior probabilities for theoretical hypotheses. The second reveals that evidence will generally induce converge to agreement among agents on the posterior probabilities of theories only if the convergence is 0 or (...)
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  49. James Hawthorne (1993). Bayesian Induction IS Eliminative Induction. Philosophical Topics 21 (1):99-138.
    Eliminative induction is a method for finding the truth by using evidence to eliminate false competitors. It is often characterized as "induction by means of deduction"; the accumulating evidence eliminates false hypotheses by logically contradicting them, while the true hypothesis logically entails the evidence, or at least remains logically consistent with it. If enough evidence is available to eliminate all but the most implausible competitors of a hypothesis, then (and only then) will the hypothesis become highly confirmed. I will argue (...)
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  50. J. Hibben (1896). Inductive Logic. Philosophical Review 5:664.
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1 — 50 / 144