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  1. How the laws of physics lie.Nancy Cartwright - 1983 - New York: Oxford University Press.
    In this sequence of philosophical essays about natural science, the author argues that fundamental explanatory laws, the deepest and most admired successes of modern physics, do not in fact describe regularities that exist in nature. Cartwright draws from many real-life examples to propound a novel distinction: that theoretical entities, and the complex and localized laws that describe them, can be interpreted realistically, but the simple unifying laws of basic theory cannot.
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  • Models as Mediators: Perspectives on Natural and Social Science.Mary S. Morgan & Margaret Morrison (eds.) - 1999 - Cambridge University Press.
    Models as Mediators discusses the ways in which models function in modern science, particularly in the fields of physics and economics. Models play a variety of roles in the sciences: they are used in the development, exploration and application of theories and in measurement methods. They also provide instruments for using scientific concepts and principles to intervene in the world. The editors provide a framework which covers the construction and function of scientific models, and explore the ways in which they (...)
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  • The Structure of scientific theories.Frederick Suppe (ed.) - 1974 - Urbana,: University of Illinois Press.
    Suppe, F. The search for philosophic understanding of scientific theories (p. [1]-241)--Proceedings of the symposium.--Bibliography, compiled by Rew A. Godow, Jr. (p. [615]-646).
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  • (1 other version)Models and Analogies in Science.Mary Hesse - 1965 - British Journal for the Philosophy of Science 16 (62):161-163.
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  • The Evolution of Cooperation.Robert M. Axelrod - 1984 - Basic Books.
    The 'Evolution of Cooperation' addresses a simple yet age-old question; If living things evolve through competition, how can cooperation ever emerge? Despite the abundant evidence of cooperation all around us, there existed no purely naturalistic answer to this question until 1979, when Robert Axelrod famously ran a computer tournament featuring a standard game-theory exercise called The Prisoner's Dilemma. To everyone's surprise, the program that won the tournament, named Tit for Tat, was not only the simplest but the most "cooperative" entrant. (...)
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  • (1 other version)Models and Analogies in Science.Mary B. Hesse - 1966 - Philosophy and Rhetoric 3 (3):190-191.
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  • The Structure of Scientific Theories.Frederick Suppe - 1977 - Critica 11 (31):138-140.
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  • Explaining Science.Ronald Giere - 1991 - Noûs 25 (3):386-388.
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  • The Structure of Scientific Theories.Peter Skagestad - 1981 - Noûs 15 (2):234-239.
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  • Explaining Science: A Cognitive Approach. [REVIEW]Jeffrey S. Poland - 1988 - Philosophical Review 100 (4):653-656.
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  • The Role Of Models In Computer Science.James H. Fetzer - 1999 - The Monist 82 (1):20-36.
    Taking Brian Cantwell Smith’s study, “Limits of Correctness in Computers,” as its point of departure, this article explores the role of models in computer science. Smith identifies two kinds of models that play an important role, where specifications are models of problems and programs are models of possible solutions. Both presuppose the existence of conceptualizations as ways of conceiving the world “in certain delimited ways.” But high-level programming languages also function as models of virtual (or abstract) machines, while low-level programming (...)
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  • Models rule, OK? A reply to Fetzer.P. N. Johnson-Laird & Ruth M. J. Byrne - 1999 - Minds and Machines 9 (1):111-118.
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  • Explanation by computer simulation in cognitive science.Jordi Fernández - 2003 - Minds and Machines 13 (2):269-284.
    My purpose in this essay is to clarify the notion of explanation by computer simulation in artificial intelligence and cognitive science. My contention is that computer simulation may be understood as providing two different kinds of explanation, which makes the notion of explanation by computer simulation ambiguous. In order to show this, I shall draw a distinction between two possible ways of understanding the notion of simulation, depending on how one views the relation in which a computing system that performs (...)
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  • Kinds of Models.Adam Morton & Mauricio Suárez - 2001 - In Malcolm G. Anderson & Paul D. Bates (eds.), Model Validation: perspectives in hydrological science. Wiley. pp. 11-22.
    We separate metaphysical from epistemic questions in the evaluation of models, taking into account the distinctive functions of models as opposed to theories. The examples a\are very varied.
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  • Mental models: Reasoning without rules. [REVIEW]James H. Fetzer - 1999 - Minds and Machines 9 (1):119-126.
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