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  1. How to Tell When Simpler, More Unified, or Less A D Hoc Theories Will Provide More Accurate Predictions.Malcolm R. Forster & Elliott Sober - 1994 - British Journal for the Philosophy of Science 45 (1):1-35.
    Traditional analyses of the curve fitting problem maintain that the data do not indicate what form the fitted curve should take. Rather, this issue is said to be settled by prior probabilities, by simplicity, or by a background theory. In this paper, we describe a result due to Akaike [1973], which shows how the data can underwrite an inference concerning the curve's form based on an estimate of how predictively accurate it will be. We argue that this approach throws light (...)
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  • Satisficing as a Humanly Rational Strategy.David Schmidtz - 2004 - In Michael Byron (ed.), Satisficing and Maximizing: Moral Theorists on Practical Reason. Cambridge University Press. pp. 30--59.
     
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  • Decision Theory and Cognitive Choice.John R. Welch - 2011 - European Journal for Philosophy of Science 1 (2):147-172.
    The focus of this study is cognitive choice: the selection of one cognitive option (a hypothesis, a theory, or an axiom, for instance) rather than another. The study proposes that cognitive choice should be based on the plausibilities of states posited by rival cognitive options and the utilities of these options' information outcomes. The proposal introduces a form of decision theory that is novel because comparative; it permits many choices among cognitive options to be based on merely comparative plausibilities and (...)
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  • Unreliable Probabilities, Risk Taking, and Decision Making.Peter Gärdenfors & Nils-Eric Sahlin - 1982 - Synthese 53 (3):361-386.
  • Rational Prediction.Wesley C. Salmon - 1981 - British Journal for the Philosophy of Science 32 (2):115-125.
  • Why Did Einstein's Programme Supersede Lorentz's? (II).Elie Zahar - 1973 - British Journal for the Philosophy of Science 24 (3):223-262.
  • Assessing Theories, Bayes Style.Franz Huber - 2008 - Synthese 161 (1):89-118.
    The problem addressed in this paper is “the main epistemic problem concerning science”, viz. “the explication of how we compare and evaluate theories [...] in the light of the available evidence” (van Fraassen, BC, 1983, Theory comparison and relevant Evidence. In J. Earman (Ed.), Testing scientific theories (pp. 27–42). Minneapolis: University of Minnesota Press). Sections 1– 3 contain the general plausibility-informativeness theory of theory assessment. In a nutshell, the message is (1) that there are two values a theory should exhibit: (...)
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  • Prediction, Probability, and Pragmatics.Ellery Eells - 2000 - Canadian Journal of Philosophy 30 (2):183-206.
    Along with such criteria as truth, comprehensiveness, explanatory adequacy, and simplicity, philosophers of science usually also mention predictive accuracy as a criterion of theory choice. But while philosophers have devoted attention to the problem of the logical structure of scientific prediction, it seems that little attention has been devoted to the difficult question of what precisely constitutes predictive accuracy, at least ‘predictive accuracy’ in the sense in which I will discuss it here.I will in this paper discuss the role of (...)
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  • A Bayesian Theory of Rational Acceptance.Mark Kaplan - 1981 - Journal of Philosophy 78 (6):305-330.
  • Non-Deductive Logic in Mathematics.James Franklin - 1987 - British Journal for the Philosophy of Science 38 (1):1-18.
    Mathematicians often speak of conjectures as being confirmed by evidence that falls short of proof. For their own conjectures, evidence justifies further work in looking for a proof. Those conjectures of mathematics that have long resisted proof, such as Fermat's Last Theorem and the Riemann Hypothesis, have had to be considered in terms of the evidence for and against them. It is argued here that it is not adequate to describe the relation of evidence to hypothesis as `subjective', `heuristic' or (...)
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  • Objectivity, Value Judgment, and Theory Choice.Thomas S. Kuhn - 1977 - In The Essential Tension: Selected Studies in Scientific Tradition and Change. University of Chicago Press. pp. 320--39.
  • A Mathematical Theory of Communication.Claude E. Shannon - 1948 - Bell System Technical Journal 27:379–423.
  • Outline of a Theory of Strongly Semantic Information.Luciano Floridi - 2004 - Minds and Machines 14 (2):197-221.
    This paper outlines a quantitative theory of strongly semantic information (TSSI) based on truth-values rather than probability distributions. The main hypothesis supported in the paper is that the classic quantitative theory of weakly semantic information (TWSI), based on probability distributions, assumes that truth-values supervene on factual semantic information, yet this principle is too weak and generates a well-known semantic paradox, whereas TSSI, according to which factual semantic information encapsulates truth, can avoid the paradox and is more in line with the (...)
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  • Information and Inference.Isaac Levi - 1967 - Synthese 17 (1):369 - 391.
  • Tyche and Athena.Henry E. Kyburg - 1979 - Synthese 40 (3):415 - 438.
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  • Simplicity and Observability: When Are Particles Elementary?Kostas Gavroglu - 1989 - Synthese 79 (3):89 - 100.
    It is not possible to dismiss the atomistic paradigm because the proposed elementary particles are too many (and, hence, it is claimed, they do not provide a simple account of nature) or because it is not possible to observe quarks in an isolated manner. The developments in particle physics have brought about radical changes to our notions of simplicity and observability, and in this paper we elaborate on these changes. It is as a result of these changes that the present (...)
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  • Testability.Elliott Sober - 1999 - Proceedings and Addresses of the American Philosophical Association 73 (2):47-76.
    That some propositions are testable, while others are not, was a fundamental idea in the philosophical program known as logical empiricism. That program is now widely thought to be defunct. Quine’s (1953) “Two Dogmas of Empiricism” and Hempel’s (1950) “Problems and Changes in the Empiricist Criterion of Meaning” are among its most notable epitaphs. Yet, as we know from Mark Twain’s comment on an obituary that he once had the pleasure of reading about himself, the report of a death can (...)
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  • Inductive Inconsistencies.Carl Gustav Hempel - 1960 - Synthese 12 (4):439-69.
  • Why Ethical Satisficing Makes Sense and Rational Satisficing Doesn't.James Dreier - 2004 - In Michael Byron (ed.), Satisficing and Maximizing. Cambridge University Press.
     
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  • Maxificing: Life on a Budget; or, If You Would Maximize, Then Satisfice!Jan Narveson - 2004 - In Michael Byron (ed.), Satisficing and Maximizing: Moral Theorists on Practical Reason. Cambridge University Press. pp. 59--70.
     
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  • Satisficing and Optimality.Michael Byron - 1998 - Ethics 109 (1):67-93.
    It is common, though perhaps not correct, to think that practical rationality is strictly instrumental.1 The functions of instrumental reason include finding suitable means to our determinate ends, helping to determine our indeterminate ends, and implementing our principles in appropriate actions. One reason that might be given for adopting instrumentalism with respect to rationality might be that our best scientific evidence offers little support for the idea that our brains have powers to detect good and bad as such in persons, (...)
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  • Great Expectations. Part II: Generalized Expected Utility as a Universal Decision Rule.Francis C. Chu & Joseph Y. Halpern - 2004 - Artificial Intelligence 159 (1-2):207-229.
  • Why Did Einstein's Programme Supersede Lorentz's? (I).Elie Zahar - 1973 - British Journal for the Philosophy of Science 24 (2):95-123.
  • Akaike Information Criterion, Curve-Fitting, and the Philosophical Problem of Simplicity.I. A. Kieseppä - 1997 - British Journal for the Philosophy of Science 48 (1):21-48.
    The philosophical significance of the procedure of applying Akaike Information Criterion (AIC) to curve-fitting problems is evaluated. The theoretical justification for using AIC (the so-called Akaike's theorem) is presented in a rigorous way, and its range of validity is assessed by presenting both instances in which it is valid and counter-examples in which it is invalid. The philosophical relevance of the justification that this result gives for making one particular choice between simple and complicated hypotheses is emphasized. In addition, recent (...)
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  • Instrumentalism, Parsimony, and the Akaike Framework.Elliott Sober - 2002 - Proceedings of the Philosophy of Science Association 2002 (3):S112-S123.
    Akaike’s framework for thinking about model selection in terms of the goal of predictive accuracy and his criterion for model selection have important philosophical implications. Scientists often test models whose truth values they already know, and they often decline to reject models that they know full well are false. Instrumentalism helps explain this pervasive feature of scientific practice, and Akaike’s framework helps provide instrumentalism with the epistemology it needs. Akaike’s criterion for model selection also throws light on the role of (...)
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  • Infrared Metaphysics: Radiation and Theory-Choice. Part 2.Hasok Chang & Sabina Leonelli - 2005 - Studies in History and Philosophy of Science Part A 36 (4):687-706.
    We continue our discussion of the competing arguments in favour of the unified theory and the pluralistic theory of radiation advanced by three nineteenth-century pioneers: Herschel, Melloni, and Draper. Our narrative is structured by a consideration of the epistemic criteria relevant to theory-choice; the epistemic focus highlights many little-known aspects of this relatively well-known episode. We argue that the acceptance of light-heat unity in this period cannot be credibly justified on the basis of common evaluative criteria such as simplicity and (...)
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  • Occam’s Razor in Science: A Case Study From Biogeography.A. Baker - 2007 - Biology and Philosophy 22 (2):193-215.
  • A Simplification of the Theory of Simplicity.Samuel A. Richmond - 1996 - Synthese 107 (3):373 - 393.
    Nelson Goodman has constructed two theories of simplicity: one of predicates; one of hypotheses. I offer a simpler theory by generalization and abstraction from his. Generalization comes by dropping special conditions Goodman imposes on which unexcluded extensions count as complicating and which excluded extensions count as simplifying. Abstraction is achieved by counting only nonisomorphic models and subinterpretations. The new theory takes into account all the hypotheses of a theory in assessing its complexity, whether they were projected prior to, or result (...)
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  • Probabilism.Bruno De Finetti - 1989 - Erkenntnis 31 (2-3):169-223.
  • Adversus mathematicos.VÍctor SÁnchez De Zavala - 1962 - Revista de Filosofía (Madrid) 21 (81):301.
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  • Great Expectations. Part I: On the Customizability of Generalized Expected Utility. [REVIEW]Francis C. Chu & Joseph Y. Halpern - 2008 - Theory and Decision 64 (1):1-36.
    We propose a generalization of expected utility that we call generalized EU (GEU), where a decision maker’s beliefs are represented by plausibility measures and the decision maker’s tastes are represented by general (i.e., not necessarily real-valued) utility functions. We show that every agent, “rational” or not, can be modeled as a GEU maximizer. We then show that we can customize GEU by selectively imposing just the constraints we want. In particular, we show how each of Savage’s postulates corresponds to constraints (...)
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  • Real-Life Decisions and Decision Theory.John R. Welch - 2012 - In Sabine Roeser, Rafaela Hillerbrand, Per Sandin & Martin Peterson (eds.), Handbook of Risk Theory. Springer.
    Some decisions result in cognitive consequences such as information gained and information lost. The focus of this study, however, is decisions with consequences that are partly or completely noncognitive. These decisions are typically referred to as ‘real-life decisions’. According to a common complaint, the challenges of real-life decision making cannot be met by decision theory. This complaint has at least two principal motives. One is the maximizing objection that to require agents to determine the optimal act under real-world constraints is (...)
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  • Interview with John Woods.Gabriella Pigozzi - 2009 - The Reasoner 3 (3):1-4.
  • The Appraisal of Theories: Kuhn Meets Bayes.Wesley C. Salmon - 1990 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1990:325 - 332.
    This paper claims that adoption of Bayes's theorem as the schema for the appraisal of scientific theories can greatly reduce the distance between Kuhnians and logical empiricists. It is argued that plausibility considerations, which Kuhn considered outside of the logic of science, can be construed as prior probabilities, which play an indispensable role in the logic of science. Problems concerning likelihoods, especially the likelihood on the "catchall," are also considered. Severe difficulties concerning the significance of this probability arise in the (...)
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  • On Semantic Information.Jaakko Hintikka - 1970 - In Hermann Bondi, Wolfgang Yourgrau & Allen duPont Breck (eds.), Physics, Logic, and History. New York: Plenum Press. pp. 147--172.
  • Surface Information and Depth Information.Jaakko Hintikka - 1970 - In Jaakko Hintikka & O. Suppes (eds.), Information and Inference. Dordrecht: Reidel.
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  • Reflections on My Critics.Ts Khn - 1970 - In Imre Lakatos & Alan Musgrave (eds.), Criticism and the Growth of Knowledge. Cambridge University Press.
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