Search results for 'Jeffrey Shallit' (try it on Scholar)

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  1. Wesley Elsberry & Jeffrey Shallit (2011). Information Theory, Evolutionary Computation, and Dembski's "Complex Specified Information". Synthese 178 (2):237 - 270.score: 240.0
    Intelligent design advocate William Dembski has introduced a measure of information called "complex specified information", or CSI. He claims that CSI is a reliable marker of design by intelligent agents. He puts forth a "Law of Conservation of Information" which states that chance and natural laws are incapable of generating CSI. In particular, CSI cannot be generated by evolutionary computation. Dembski asserts that CSI is present in intelligent causes and in the flagellum of Escherichia coli, and concludes that neither have (...)
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  2. Richard C. Jeffrey (2004). Formal Logic: Its Scope and Limits. Hackett Pub..score: 60.0
    This brief paperback is designed for symbolic/formal logic courses. It features the tree method proof system developed by Jeffrey. The new edition contains many more examples and exercises and is reorganized for greater accessibility.
     
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  3. Richard C. Jeffrey (1992). Probability and the Art of Judgment. Cambridge University Press.score: 60.0
    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 (...)
     
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  4. Richard C. Jeffrey (1974). Preference Among Preferences. Journal of Philosophy 71 (13):377-391.score: 30.0
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  5. Richard C. Jeffrey (1956). Valuation and Acceptance of Scientific Hypotheses. Philosophy of Science 23 (3):237-246.score: 30.0
  6. Richard C. Jeffrey (1975). Probability and Falsification: Critique of the Popper Program. Synthese 30 (1-2):95 - 117.score: 30.0
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  7. Andrew Jeffrey (1979). Polemarchus and Socrates on Justice and Harm. Phronesis 24 (1):54 - 69.score: 30.0
  8. Richard Jeffrey, Revenge of Wolfman: A Probabilistic Explication of Full Belief.score: 30.0
    "To some people, life is very simple . . . no shadings and grays, all blacks and whites. . . . Now, others of us find that good, bad, right, wrong, are many-sided, complex things. We try to see every side; but the more we see, the less sure we are.".
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  9. Richard Jeffrey (1987). Indefinite Probability Judgment: A Reply to Levi. Philosophy of Science 54 (4):586-591.score: 30.0
    Isaac Levi and I have different views of probability and decision making. Here, without addressing the merits, I will try to answer some questions recently asked by Levi (1985) about what my view is, and how it relates to his.
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  10. Richard Jeffrey (1996). Unknown Probabilities. Erkenntnis 45 (2-3):327 - 335.score: 30.0
    From a point of view like de Finetti's, what is the judgmental reality underlying the objectivistic claim that a physical magnitude X determines the objective probability that a hypothesis H is true? When you have definite conditional judgmental probabilities for H given the various unknown values of X, a plausible answer is sufficiency, i.e., invariance of those conditional probabilities as your probability distribution over the values of X varies. A different answer, in terms of conditional exchangeability, is offered for use (...)
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  11. Richard C. Jeffrey (1991). After Carnap. Erkenntnis 35 (1-3):255 - 262.score: 30.0
  12. Richard C. Jeffrey (1973). Carnap's Inductive Logic. Synthese 25 (3-4):299 - 306.score: 30.0
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  13. Richard C. Jeffrey (1971). On Interpersonal Utility Theory. Journal of Philosophy 68 (20):647-656.score: 30.0
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  14. Richard Jeffrey (1993). Take Back the Day! Jon Dorling's Bayesian Solution of the Duhem Problem. Philosophical Issues 3:197-207.score: 30.0
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  15. Richard Jeffrey (1981). The Logic of Decision Defended. Synthese 48 (3):473 - 492.score: 30.0
    The approach to decision theory floated in my 1965 book is reviewed (I), challenged in various related ways (II–V) and defended, firstad hoc (II–IV) and then by a general argument of Ellery Ells's (VI). Finally, causal decision theory (in a version sketched in VII) is exhibited as a special case of my 1965 theory, according to the Eellsian argument.
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  16. Richard Jeffrey (1995). A Brief Guide to the Work of Carl Gustav Hempel. Erkenntnis 42 (1):3 - 7.score: 30.0
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  17. Richard Jeffrey (1987). Alias Smith and Jones: The Testimony of the Senses. [REVIEW] Erkenntnis 26 (3):391 - 399.score: 30.0
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  18. Richard C. Jeffrey (1965). Ethics and the Logic of Decision. Journal of Philosophy 62 (19):528-539.score: 30.0
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  19. Richard Jeffrey (2002). Logicism Lite. Philosophy of Science 69 (3):474-496.score: 30.0
    Logicism Lite counts number‐theoretical laws as logical for the same sort of reason for which physical laws are counted as as empirical: because of the character of the data they are responsible to. In the case of number theory these are the data verifying or falsifying the simplest equations, which Logicism Lite counts as true or false depending on the logical validity or invalidity of first‐order argument forms in which no numbertheoretical notation appears.
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  20. Richard Jeffrey (1992). Radical Probabilism (Prospectus for a User's Manual). Philosophical Issues 2:193-204.score: 30.0
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  21. Richard Jeffrey (1986). Probabilism and Induction. Topoi 5 (1):51-58.score: 30.0
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  22. Richard Jeffrey (1995). Probability Reparation: The Problem of New Explanation. [REVIEW] Philosophical Studies 77 (1):97 - 101.score: 30.0
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  23. Richard C. Jeffrey (1977). A Note on the Kinematics of Preference. Erkenntnis 11 (1):135 - 141.score: 30.0
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  24. Richard C. Jeffrey (1966). Goodman's Query. Journal of Philosophy 63 (11):281-288.score: 30.0
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  25. Richard Jeffrey (1984). De Finetti's Probabilism. Synthese 60 (1):73 - 90.score: 30.0
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  26. Richard C. Jeffrey (1964). Popper on the Rule of Succession. Mind 73 (289):129.score: 30.0
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  27. Richard Jeffrey (1997). In Memoriam: Carl Gustav Hempel. [REVIEW] Erkenntnis 47 (3):281-283.score: 30.0
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  28. Richard C. Jeffrey (1963). On Indeterminate Conditionals. Philosophical Studies 14 (3):37 - 43.score: 30.0
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  29. Richard C. Jeffrey (1975). Replies. Synthese 30 (1-2):149 - 157.score: 30.0
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  30. Maria Carla Galavotti & Richard Jeffrey (1989). Preface. Erkenntnis 31 (2-3):165-167.score: 30.0
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  31. Richard Jeffrey (1989). Reading Probabilismo. Erkenntnis 31 (2-3):225 - 237.score: 30.0
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  32. Richard C. Jeffrey (1968). The Whole Truth. Synthese 18 (1):24 - 27.score: 30.0
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  33. Richard C. Jeffrey (1959). A Note on Finch's "an Explication of Counterfactuals by Probability Theory". Philosophy and Phenomenological Research 20 (1):116.score: 30.0
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  34. Lydia McGrew (2014). Jeffrey Conditioning, Rigidity, and the Defeasible Red Jelly Bean. Philosophical Studies 168 (2):569-582.score: 24.0
    Jonathan Weisberg has argued that Jeffrey Conditioning is inherently “anti-holistic” By this he means, inter alia, that JC does not allow us to take proper account of after-the-fact defeaters for our beliefs. His central example concerns the discovery that the lighting in a room is red-tinted and the relationship of that discovery to the belief that a jelly bean in the room is red. Weisberg’s argument that the rigidity required for JC blocks the defeating role of the red-tinted light (...)
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  35. Ilho Park (2013). Simultaneous Belief Updates Via Successive Jeffrey Conditionalization. Synthese 190 (16):3511-3533.score: 24.0
    This paper discusses simultaneous belief updates. I argue here that modeling such belief updates using the Principle of Minimum Information can be regarded as applying Jeffrey conditionalization successively, and so that, contrary to what many probabilists have thought, the simultaneous belief updates can be successfully modeled by means of Jeffrey conditionalization.
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  36. Jeffrey Church (2014). Nietzsche, Nihilism, and the Philosophy of the Future Ed. By Jeffrey Metzger (Review). Journal of Nietzsche Studies 44 (3):495-497.score: 21.0
    In his introduction, Jeffrey Metzger states that “at some point in the past 20 or 30 years … Nietzsche’s name [became] no longer associated primarily with nihilism” (1). Metzger is pointing to the increasing contemporary scholarly interest in Nietzsche’s epistemology, naturalism, and metaethics. The worthy aim of this volume is to ask us to examine once again the underlying philosophical problem to which these views are a response, namely, nihilism. This volume helpfully reminds us that Nietzsche’s philosophical motivation still (...)
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  37. Hartry Field (1978). A Note on Jeffrey Conditionalization. Philosophy of Science 45 (3):361-367.score: 18.0
    Bayesian decision theory can be viewed as the core of psychological theory for idealized agents. To get a complete psychological theory for such agents, you have to supplement it with input and output laws. On a Bayesian theory that employs strict conditionalization, the input laws are easy to give. On a Bayesian theory that employs Jeffrey conditionalization, there appears to be a considerable problem with giving the input laws. However, Jeffrey conditionalization can be reformulated so that the problem (...)
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  38. Alan Hájek (2006). In Memory of Richard Jeffrey: Some Reminiscences and Some Reflections onThe Logic of Decision. Philosophy of Science 73 (5):947-958.score: 18.0
    This paper is partly a tribute to Richard Jeffrey, partly a reflection on some of his writings, The Logic of Decision in particular. I begin with a brief biography and some fond reminiscences of Dick. I turn to some of the key tenets of his version of Bayesianism. All of these tenets are deployed in my discussion of his response to the St. Petersburg paradox, a notorious problem for decision theory that involves a game of infinite expectation. Prompted by (...)
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  39. Glenn Shafer (1981). Jeffrey's Rule of Conditioning. Philosophy of Science 48 (3):337-362.score: 18.0
    Richard Jeffrey's generalization of Bayes' rule of conditioning follows, within the theory of belief functions, from Dempster's rule of combination and the rule of minimal extension. Both Jeffrey's rule and the theory of belief functions can and should be construed constructively, rather than normatively or descriptively. The theory of belief functions gives a more thorough analysis of how beliefs might be constructed than Jeffrey's rule does. The inadequacy of Bayesian conditioning is much more general than Jeffrey's (...)
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  40. Hans Joas (1988). The Antinomies of Neofunctionalism: A Critical Essay on Jeffrey Alexander. Inquiry 31 (4):471 – 494.score: 18.0
    Since the beginning of the ?eighties of the present century, a circle of relatively young American sociologists who are followers of Jeffrey Alexander are making energetic and spectacular efforts to supply sociology with a uniform and comprehensive theoretical framework by continuing Talcott Parsons' lifework. The present article is an appreciation of Alexander's achievements in the justification of a general sociological theory (especially a theory of action and social order) while pointing to objections that can be raised against the character (...)
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  41. Marcelo Tsuji (2000). Partial Structures and Jeffrey-Keynes Algebras. Synthese 125 (1-2):283-299.score: 18.0
    In Tsuji 1997 the concept of Jeffrey-Keynes algebras was introduced in order to construct a paraconsistent theory of decision under uncertainty. In the present paper we show that these algebras can be used to develop a theory of decision under uncertainty that measures the degree of belief on the quasi (or partial) truth of the propositions. As applications of this new theory of decision, we use it to analyze Popper's paradox of ideal evidence and to indicate a possible way (...)
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  42. Carl Wagner, Jeffrey Conditioning and External Bayesianity.score: 18.0
    Abstract. Suppose that several individuals who have separately assessed prior probability distributions over a set of possible states of the world wish to pool their individual distributions into a single group distribution, while taking into account jointly perceived new evidence. They have the option of (i) first updating their individual priors and then pooling the resulting posteriors or (ii) first pooling their priors and then updating the resulting group prior. If the pooling method that they employ is such that they (...)
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  43. Nicholas Wolterstorff (2005). Jeffrey Stout on Democracy and its Contemporary Christian Critics. Journal of Religious Ethics 33 (4):633-647.score: 18.0
    Jeffrey Stout addresses two of the main criticisms of liberal democracy by its contemporary neotraditionalist Christian critics: that liberal democracy is destructive of social tradition, and thereby of virtue in the citizenry, and that liberal democracy is inherently secular, committed to expunging religious voices from the public arena. I judge that Stout effectively answers these charges: liberal democracy has its own tradition, it cultivates the virtues relevant to that, and it is not inherently hostile to piety. What Stout does (...)
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  44. Virginia Moyer, Steven M. Teutsch & Jeffrey R. Botkin (2009). Virginia Moyer, Steven M. Teutsch, and Jeffrey R. Botkin Reply. Hastings Center Report 39 (1):7-8.score: 18.0
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  45. Don Browning (2008). Love as Sacrifice, Love as Mutuality: Response to Jeffrey Tillman. Zygon 43 (3):557-562.score: 18.0
    Jeffrey Tillman is perceptive in noticing that certain Protestant theologians have used evolutionary theory to become more sympathetic to Roman Catholic views of Christian love. But he is incorrect in saying that these formulations deemphasize a place for self-sacrifice in Christian love. Christian love defined as a strenuous equal-regard for both other and self also requires sacrificial efforts to restore love as equal-regard when finitude and sin undermine genuine mutuality and community.
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  46. Daniel Osherson, Order Dependence and Jeffrey Conditionalization.score: 18.0
    A glance at the sky raises my probability of rain to .7. As it happens, the conditional probabilities of each state given rain remain the same, and similarly for their conditional probabilities given no rain. As Jeffrey (1983, Ch. 11) points out, my new distribution P2 is therefore fixed by the law of total probability. For example, P2(RC) = P2(RC | R)P2(R)+P2(RC | ¯.
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  47. Blair Henry, Mervyn Dean, Victor Cellarius & Larry Librach (2011). To "Sleep Until Death"Jeffrey T. Berger Replies:Rights Vs. LibertyDavid Orentlicher Replies. Hastings Center Report 41 (1).score: 18.0
    To the Editor: It was with great interest that our Canadian Palliative Sedation Therapy Guideline working group read Jeffrey Berger's recent article ("Rethinking Guidelines for the Use of Palliative Sedation," May-June 2010). Given our own group's efforts to develop national guidelines, we have rethought the issue of palliative sedation therapy several times over the past year.The use of clear and concise definitions is fundamental to the development of any consensus guidelines on this topic. In the article, the term "palliative (...)
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  48. Helen Hodges, Stevan Harnad, Barbara L. Finlay & Paul Bloom (2004). In Memoriam: Jeffrey Gray (1934–2004). Behavioral and Brain Sciences 27 (1):1-2.score: 18.0
    Many strands are woven into the ideas and work of Jeffrey Gray. From a background of classical languages and a spell in military intelligence spent honing skills in languages and typing, he took two BA degrees (in modern languages and psychology) at Oxford University. He then trained as a clinical psychologist at the Institute of Psychiatry (IOP), London, capping this with a PhD on the sources of emotional behaviour.
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  49. Ittay Nissan-Rozen (2013). Jeffrey Conditionalization, the Principal Principle, the Desire as Belief Thesis, and Adams's Thesis. British Journal for the Philosophy of Science 64 (4):axs039.score: 18.0
    I show that David Lewis’s principal principle is not preserved under Jeffrey conditionalization. Using this observation, I argue that Lewis’s reason for rejecting the desire as belief thesis and Adams’s thesis applies also to his own principal principle. 1 Introduction2 Adams’s Thesis, the Desire as Belief Thesis, and the Principal Principle3 Jeffrey Conditionalization4 The Principal Principles Not Preserved under Jeffrey Conditionalization5 Inadmissible Experiences.
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  50. David E. Over & Constantinos Hadjichristidis (2009). Uncertain Premises and Jeffrey's Rule. Behavioral and Brain Sciences 32 (1):97-98.score: 18.0
    Oaksford & Chater (O&C) begin in the halfway Bayesian house of assuming that minor premises in conditional inferences are certain. We demonstrate that this assumption is a serious limitation. They additionally suggest that appealing to Jeffrey's rule could make their approach more general. We present evidence that this rule is not limited enough to account for actual probability judgements.
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