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  1. On Computable Numbers, with an Application to the Entscheidungsproblem.Alan Turing - 1936 - Proceedings of the London Mathematical Society 42 (1):230-265.
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  • (1 other version)The devil in the details: asymptotic reasoning in explanation, reduction, and emergence.Robert W. Batterman - 2002 - New York: Oxford University Press.
    Robert Batterman examines a form of scientific reasoning called asymptotic reasoning, arguing that it has important consequences for our understanding of the scientific process as a whole. He maintains that asymptotic reasoning is essential for explaining what physicists call universal behavior. With clarity and rigor, he simplifies complex questions about universal behavior, demonstrating a profound understanding of the underlying structures that ground them. This book introduces a valuable new method that is certain to fill explanatory gaps across disciplines.
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  • Statistical explanation and ergodic theory.Lawrence Sklar - 1973 - Philosophy of Science 40 (2):194-212.
    Some philosphers of science of an empiricist and pragmatist bent have proposed models of statistical explanation, but have then become sceptical of the adequacy of these models. It is argued that general considerations concerning the purpose of function of explanation in science which are usually appealed to by such philosophers show that their scepticism is not well taken; for such considerations provide much the same rationale for the search for statistical explanations, as these philosophers have characterized them, as they do (...)
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  • Defining chaos.Robert W. Batterman - 1993 - Philosophy of Science 60 (1):43-66.
    This paper considers definitions of classical dynamical chaos that focus primarily on notions of predictability and computability, sometimes called algorithmic complexity definitions of chaos. I argue that accounts of this type are seriously flawed. They focus on a likely consequence of chaos, namely, randomness in behavior which gets characterized in terms of the unpredictability or uncomputability of final given initial states. In doing so, however, they can overlook the definitive feature of dynamical chaos--the fact that the underlying motion generating the (...)
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  • Models, confirmation, and chaos.Jeffrey Koperski - 1998 - Philosophy of Science 65 (4):624-648.
    The use of idealized models in science is by now well-documented. Such models are typically constructed in a “top-down” fashion: starting with an intractable theory or law and working down toward the phenomenon. This view of model-building has motivated a family of confirmation schemes based on the convergence of prediction and observation. This paper considers how chaotic dynamics blocks the convergence view of confirmation and has forced experimentalists to take a different approach to model-building. A method known as “phase space (...)
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  • Explaining Chaos.Peter Smith - 1998 - Cambridge University Press.
    Chaotic dynamics has been hailed as the third great scientific revolution in physics this century, comparable to relativity and quantum mechanics. In this book, Peter Smith takes a cool, critical look at such claims. He cuts through the hype and rhetoric by explaining some of the basic mathematical ideas in a clear and accessible way, and by carefully discussing the methodological issues which arise. In particular, he explores the new kinds of explanation of empirical phenomena which modern dynamics can deliver. (...)
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  • Determinism, Predictability and Chaos.G. M. K. Hunt - 1987 - Analysis 47 (3):129 - 133.
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  • Chaos, prediction and laplacean determinism.M. A. Stone - 1989 - American Philosophical Quarterly 26 (2):123--31.
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  • Simple theories of a messy world: Truth and explanatory power in nonlinear dynamics.Alexander Rueger & W. David Sharp - 1996 - British Journal for the Philosophy of Science 47 (1):93-112.
    Philosophers like Duhem and Cartwright have argued that there is a tension between laws' abilities to explain and to represent. Abstract laws exemplify the first quality, phenomenological laws the second. This view has both metaphysical and methodological aspects: the world is too complex to be represented by simple theories; supplementing simple theories to make them represent reality blocks their confirmation. We argue that both aspects are incompatible with recent developments in nonlinear dynamics. Confirmation procedures and modelling strategies in nonlinear dynamics (...)
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  • Explaining Chaos.Peter Smith - 2000 - Philosophical Quarterly 50 (198):126-128.
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  • Regularity in nonlinear dynamical systems.D. Lynn Holt & R. Glynn Holt - 1993 - British Journal for the Philosophy of Science 44 (4):711-727.
    Laws of nature have been traditionally thought to express regularities in the systems which they describe, and, via their expression of regularities, to allow us to explain and predict the behavior of these systems. Using the driven simple pendulum as a paradigm, we identify three senses that regularity might have in connection with nonlinear dynamical systems: periodicity, uniqueness, and perturbative stability. Such systems are always regular only in the second of these senses, and that sense is not robust enough to (...)
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  • Computable chaos.John A. Winnie - 1992 - Philosophy of Science 59 (2):263-275.
    Some irrational numbers are "random" in a sense which implies that no algorithm can compute their decimal expansions to an arbitrarily high degree of accuracy. This feature of (most) irrational numbers has been claimed to be at the heart of the deterministic, but chaotic, behavior exhibited by many nonlinear dynamical systems. In this paper, a number of now classical chaotic systems are shown to remain chaotic when their domains are restricted to the computable real numbers, providing counterexamples to the above (...)
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  • On the Incompleteness of Axiomatized Models for the Empirical Sciences.Newton C. A. da Costa & Francisco Antonio Doria - 1992 - Philosophica 50.
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