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  1. Multiple Analogies in Science and Philosophy.Cameron Shelley - 2003 - John Benjamins Publishing.
    A multiple analogy is a structured comparison in which several sources are likened to a target. In "Multiple analogies in science and philosophy," Shelley provides a thorough account of the cognitive representations and processes that participate in multiple analogy formation. Through analysis of real examples taken from the fields of evolutionary biology, archaeology, and Plato's "Republic," Shelley argues that multiple analogies are not simply concatenated single analogies but are instead the general form of analogical inference, of which single analogies are (...)
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  • Introduction.Lorenzo Magnani, Nancy Nersessian & Paul Thagard - 1998 - Philosophica 61 (1):51-76.
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  • Representation and productive ambiguity in mathematics and the sciences.Emily Grosholz - 2007 - New York: Oxford University Press.
    Viewed this way, the texts yield striking examples of language and notation that are irreducibly ambiguous and productive because they are ambiguous.
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  • Creation and Discovery in Mathematics.Mary Leng - 2011 - In John Polkinghorne (ed.), Meaning in mathematics. New York: Oxford University Press.
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  • A Role for Representation Theorems†.Emiliano Ippoliti - 2018 - Philosophia Mathematica 26 (3):396-412.
    I argue that the construction of representation theorems is a powerful tool for creating novel objects and theories in mathematics, as the construction of a new representation introduces new pieces of information in a very specific way that enables a solution for a problem and a proof of a new theorem. In more detail I show how the work behind the proof of a representation theorem transforms a mathematical problem in a way that makes it tractable and introduces information into (...)
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  • Ways of Advancing Knowledge. A Lesson from Knot Theory and Topology.Emiliano Ippoliti - 2016 - In Emiliano Ippoliti, Fabio Sterpetti & Thomas Nickles (eds.), Models and Inferences in Science. Cham: Springer. pp. 147--172.
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  • Rethinking Logic: Logic in Relation to Mathematics, Evolution, and Method.Carlo Cellucci - 2013 - Dordrecht, Netherland: Springer.
    This volume examines the limitations of mathematical logic and proposes a new approach to logic intended to overcome them. To this end, the book compares mathematical logic with earlier views of logic, both in the ancient and in the modern age, including those of Plato, Aristotle, Bacon, Descartes, Leibniz, and Kant. From the comparison it is apparent that a basic limitation of mathematical logic is that it narrows down the scope of logic confining it to the study of deduction, without (...)
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  • Mathematics and Plausible Reasoning: Induction and analogy in mathematics.George Pólya - 1954 - Princeton, NJ, USA: Princeton University Press.
    Here the author of How to Solve It explains how to become a "good guesser." Marked by G. Polya's simple, energetic prose and use of clever examples from a wide range of human activities, this two-volume work explores techniques of guessing, inductive reasoning, and reasoning by analogy, and the role they play in the most rigorous of deductive disciplines.
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  • Models and Analogies in Science.Mary B. Hesse - 1963 - [Notre Dame, Ind.]: University of Notre Dame Press.
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  • Multiple Roles for Analogies in the Genesis of Fluid Mechanics: How Analogies Can Cooperate with Other Heuristic Strategies.Alain Ulazia - 2016 - Foundations of Science 21 (4):543-565.
    When Johann and Daniel Bernoulli founded fluid dynamics they encountered several problems. To go beyond the vision of Newtonian particles, a new set of images was needed in order to deal with the spatial extensibility and lack of form of fluids. I point to evidence that analogy was an essential abductive strategy in the creation of this imagery. But its heuristic behavior is complex: analogy can provide an initial model or proto-model that establishes the starting point of a theoretical process, (...)
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  • Models and Inferences in Science.Emiliano Ippoliti, Fabio Sterpetti & Thomas Nickles (eds.) - 2016 - Cham: Springer.
    The book answers long-standing questions on scientific modeling and inference across multiple perspectives and disciplines, including logic, mathematics, physics and medicine. The different chapters cover a variety of issues, such as the role models play in scientific practice; the way science shapes our concept of models; ways of modeling the pursuit of scientific knowledge; the relationship between our concept of models and our concept of science. The book also discusses models and scientific explanations; models in the semantic view of theories; (...)
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  • Mathematics and Plausible Reasoning.D. van Dantzig - 1959 - Synthese 11 (4):353-358.
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  • What is a problem that we may solve it.Thomas Nickles - 1981 - Synthese 47 (1):85 - 118.
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  • Introduction.Lorenzo Magnani, Nancy Nersessian & Paul Thagard - 1998 - Philosophica 61 (1).
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  • Scientific Discovery: Computational Explorations of the Creative Process. Pat Langley, Herbert A. Simon, Gary L. Bradshaw, Jan M. Zytkow.Malcolm R. Forster - 1990 - Philosophy of Science 57 (2):336-338.
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  • Proofs and Refutations: The Logic of Mathematical Discovery.Daniel Isaacson - 1978 - Philosophical Quarterly 28 (111):169-171.
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  • Scientific Discovery, Computational Explorations of the Creative Processes. [REVIEW]W. Balzer - 1991 - Erkenntnis 34 (1):125-127.
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  • Models and Analogies in Science.Mary B. Hesse - 1966 - Philosophy and Rhetoric 3 (3):190-191.
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  • Models and Analogies in Science.Mary Hesse - 1965 - British Journal for the Philosophy of Science 16 (62):161-163.
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  • Proofs and Refutations: The Logic of Mathematical Discovery.Imre Lakatos, John Worrall & Elie Zahar - 1978 - Mind 87 (346):314-316.
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  • Representation and Productive Ambiguity in Mathematics and the Sciences.Emily R. Grosholz - 2006 - Studia Leibnitiana 38 (2):244-246.
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  • Proofs and Refutations. The Logic of Mathematical Discovery.I. Lakatos - 1977 - Tijdschrift Voor Filosofie 39 (4):715-715.
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