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Profile: Malcolm Forster (University of Wisconsin, Madison)
  1. Malcolm R. Forster, I. A. Kieseppä, Dan Hausman, Alexei Krioukov, Stephen Leeds, Alan Macdonald & Larry Shapiro (forthcoming). The Conceptual Role of 'Temperature'in Statistical Mechanics: Or How Probabilistic Averages Maximize Predictive Accuracy. Philosophy of Science.
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  2. Malcolm R. Forster (2011). Scientific Evidence. In Steven French & Juha Saatsi (eds.), Continuum Companion to the Philosophy of Science. Continuum. 179.
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  3. Malcolm R. Forster (2010). Miraculous Consilience of Quantum Mechanics. In. In Ellery Eells & James Fetzer (eds.), The Place of Probability in Science. Springer. 201--228.
  4. Cristina Bicchieri, Jason McKenzie Alexander, Kevin T. Kelly, Kevin Js Zollman, Malcolm R. Forster, Predrag Šustar, Patrick Forber, Kenneth Reisman, Jay Odenbaugh & Yoichi Ishida (2007). 10. Philosophy of Chemistry. Philosophy of Science 74 (5).
     
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  5. Malcolm R. Forster (2006). Counterexamples to a Likelihood Theory of Evidence. Minds and Machines 16 (3):319-338.
    The likelihood theory of evidence (LTE) says, roughly, that all the information relevant to the bearing of data on hypotheses (or models) is contained in the likelihoods. There exist counterexamples in which one can tell which of two hypotheses is true from the full data, but not from the likelihoods alone. These examples suggest that some forms of scientific reasoning, such as the consilience of inductions (Whewell, 1858. In Novum organon renovatum (Part II of the 3rd ed.). The philosophy of (...)
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  6. Malcolm R. Forster & Alexey Kryukov (2003). The Emergence of the Macroworld: A Study of Intertheory Relations in Classical and Quantum Mechanics. Philosophy of Science 70 (5):1039-1051.
    Classical mechanics is empirically successful because the probabilistic mean values of quantum mechanical observables follow the classical equations of motion to a good approximation (Messiah 1970, 215). We examine this claim for the one‐dimensional motion of a particle in a box, and extend the idea by deriving a special case of the ideal gas law in terms of the mean value of a generalized force used to define “pressure.” The examples illustrate the importance of probabilistic averaging as a method of (...)
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  7. Malcolm R. Forster (2002). Predictive Accuracy as an Achievable Goal of Science. Proceedings of the Philosophy of Science Association 2002 (3):S124-S134.
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  8. S. L. Zabell, Brian Skyrms, Elliott Sober, Malcolm R. Forster, Wayne C. Myrvold, William L. Harper, Rob Clifton, Itamar Pitowsky, Robyn M. Dawes & David Faust (2002). 10. It All Adds Up: The Dynamic Coherence of Radical Probabilism It All Adds Up: The Dynamic Coherence of Radical Probabilism (Pp. S98-S103). [REVIEW] Philosophy of Science 69 (S3).
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  9. Malcolm R. Forster (1999). How Do Simple Rules `Fit to Reality' in a Complex World? Minds and Machines 9 (4):543-564.
    The theory of fast and frugal heuristics, developed in a new book called Simple Heuristics that make Us Smart (Gigerenzer, Todd, and the ABC Research Group, in press), includes two requirements for rational decision making. One is that decision rules are bounded in their rationality –- that rules are frugal in what they take into account, and therefore fast in their operation. The second is that the rules are ecologically adapted to the environment, which means that they `fit to reality.' (...)
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  10. Malcolm R. Forster (1995). Bayes and Bust: Simplicity as a Problem for a Probabilist's Approach to Confirmation. [REVIEW] British Journal for the Philosophy of Science 46 (3):399-424.
    The central problem with Bayesian philosophy of science is that it cannot take account of the relevance of simplicity and unification to confirmation, induction, and scientific inference. The standard Bayesian folklore about factoring simplicity into the priors, and convergence theorems as a way of grounding their objectivity are some of the myths that Earman's book does not address adequately. 1Review of John Earman: Bayes or Bust?, Cambridge, MA. MIT Press, 1992, £33.75cloth.
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  11. Malcolm R. Forster (1995). The Golfer's Dilemma: A Reply to Kukla on Curve-Fitting. British Journal for the Philosophy of Science 46 (3):348-360.
    Curve-fitting typically works by trading off goodness-of-fit with simplicity, where simplicity is measured by the number of adjustable parameters. However, such methods cannot be applied in an unrestricted way. I discuss one such correction, and explain why the exception arises. The same kind of probabilistic explanation offers a surprising resolution to a common-sense dilemma.
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  12. Malcolm R. Forster (1994). Non-Bayesian Foundations for Statistical Estimation, Prediction, and the Ravens Example. Erkenntnis 40 (3):357 - 376.
    The paper provides a formal proof that efficient estimates of parameters, which vary as as little as possible when measurements are repeated, may be expected to provide more accurate predictions. The definition of predictive accuracy is motivated by the work of Akaike (1973). Surprisingly, the same explanation provides a novel solution for a well known problem for standard theories of scientific confirmation — the Ravens Paradox. This is significant in light of the fact that standard Bayesian analyses of the paradox (...)
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  13. Malcolm R. Forster (1990). Book Review:Scientific Discovery: Computational Explorations of the Creative Process Pat Langley, Herbert A. Simon, Gary L. Bradshaw, Jan M. Zytkow. [REVIEW] Philosophy of Science 57 (2):336-.
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  14. Malcolm R. Forster (1988). Sober's Principle of Common Cause and the Problem of Comparing Incomplete Hypotheses. Philosophy of Science 55 (4):538-559.
    Sober (1984) has considered the problem of determining the evidential support, in terms of likelihood, for a hypothesis that is incomplete in the sense of not providing a unique probability function over the event space in its domain. Causal hypotheses are typically like this because they do not specify the probability of their initial conditions. Sober's (1984) solution to this problem does not work, as will be shown by examining his own biological examples of common cause explanation. The proposed solution (...)
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  15. Malcolm R. Forster (1988). The Confirmation of Common Component Causes. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1988:3 - 9.
    This paper aims to show how Whewell's notions of consilience and unification-explicated in more modern probabilistic terms provide a satisfying treatment of cases of scientific discovery Which require the postulatioin component causes to explain complex events. The results of this analysis support the received view that the increased unification and generality of theories leads to greater testability, and confirmation if the observations are favorable. This solves a puzzle raised by Cartwright in How the Laws of Physics Lie about the nature (...)
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  16. Malcolm R. Forster (1986). Counterfactual Reasoning in the Bell-Epr Paradox. Philosophy of Science 53 (1):133-144.
    Skyrms's formulation of the argument against stochastic hidden variables in quantum mechanics using conditionals with chance consequences suffers from an ambiguity in its "conservation" assumption. The strong version, which Skyrms needs, packs in a "no-rapport" assumption in addition to the weaker statement of the "experimental facts." On the positive side, I argue that Skyrms's proof has two unnoted virtues (not shared by previous proofs): (1) it shows that certain difficulties that arise for deterministic hidden variable theories that exploit a nonclassical (...)
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  17. Malcolm R. Forster (1986). Unification and Scientific Realism Revisited. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1986:394 - 405.
    Van Fraassen has argued that quantum mechanics does not conform to the pattern of common cause explanation used by Salmon as a precise formulation of Smart's 'cosmic coincidence' argument for scientific realism. This paper adds to this list some common examples from classical physics that also do not conform to Salmon's explanatory schema. This is bad news and good news for the realist. The bad news is that Salmon's argument for realism does not work; the good news is that realism (...)
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  18. Malcolm R. Forster (1985). Book Review:How the Laws of Physics Lie Nancy Cartwright. [REVIEW] Philosophy of Science 52 (3):478-.
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  19. Malcolm R. Forster & Alexei Krioukov, How to ‘See Through’ the Ideal Gas Law in Terms of the Concepts of Quantum Mechanics.
    Textbooks in quantum mechanics frequently claim that quantum mechanics explains the success of classical mechanics because “the mean values [of quantum mechanical observables] follow the classical equations of motion to a good approximation,” while “the dimensions of the wave packet be small with respect to the characteristic dimensions of the problem.” The equations in question are Ehrenfest’s famous equations. We examine this case for the one-dimensional motion of a particle in a box, and extend the idea deriving a special case (...)
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