Results for 'Numerical modelling'

1000+ found
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  1.  20
    Numeration Models of λ‐Calculus.Akira Kanda - 1985 - Mathematical Logic Quarterly 31 (14‐18):209-220.
  2.  27
    Numeration Models of λβ‐Calculus.Akira Kanda - 1986 - Mathematical Logic Quarterly 32 (25‐30):409-414.
  3.  30
    Numeration Models of λ‐Calculus.Akira Kanda - 1985 - Mathematical Logic Quarterly 31 (14-18):209-220.
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  4.  22
    Numeration Models of λβ‐Calculus.Akira Kanda - 1986 - Mathematical Logic Quarterly 32 (25-30):409-414.
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  5.  34
    What do numerical models really represent?Gabriele Gramelsberger - 2011 - Studies in History and Philosophy of Science Part A 42 (2):296-302.
  6. Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences.Naomi Oreskes, Kristin Shrader-Frechette & Kenneth Belitz - 1994 - Science 263 (5147):641-646.
    Verification and validation of numerical models of natural systems is impossible. This is because natural systems are never closed and because model results are always nonunique. Models can be confirmed by the demonstration of agreement between observation and prediction, but confirmation is inherently partial. Complete confirmation is logically precluded by the fallacy of affirming the consequent and by incomplete access to natural phenomena. Models can only be evaluated in relative terms, and their predictive value is always open to question. (...)
     
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  7.  11
    Evidence from numerical modelling for 3D spreading of [001] screw dislocations in Mg2SiO4forsterite.Ph Carrez, A. M. Walker, A. Metsue & P. Cordier - 2008 - Philosophical Magazine 88 (16):2477-2485.
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  8.  17
    Classes of Numeration Models of λ‐Calculus.Akira Kanda - 1986 - Mathematical Logic Quarterly 32 (19‐24):315-322.
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  9.  24
    Classes of Numeration Models of λ-Calculus.Akira Kanda - 1986 - Zeitschrift fur mathematische Logik und Grundlagen der Mathematik 32 (19-24):315-322.
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  10.  7
    Athermal heterogeneous nucleation of freezing: numerical modelling for polygonal and polyhedral substrates.S. A. Reavley & A. L. Greer - 2008 - Philosophical Magazine 88 (4):561-579.
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  11.  60
    Solving Numerically Ermakov-type Equation for Newtonian Cosmology Model with Vortex.Victor Christianto, Florentin Smarandache & Yunita Umniyati - manuscript
    It has been known for long time that most of the existing cosmology models have singularity problem. Cosmological singularity has been a consequence of excessive symmetry of flow, such as “Hubble’s law”. More realistic one is suggested, based on Newtonian cosmology model but here we include the vertical-rotational effect of the whole Universe. We review a Riccati-type equation obtained by Nurgaliev, and solve the equation numerically with Mathematica. It is our hope that the new proposed method can be verified with (...)
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  12.  8
    What numerical methods are not. The case of multilayered simulations, with several computational models.Thomas Boyer - unknown
  13.  7
    Novel Numerical Estimates of the Pneumonia and Meningitis Epidemic Model via the Nonsingular Kernel with Optimal Analysis.Saima Rashid, Bushra Kanwal, Abdulaziz Garba Ahmad, Ebenezer Bonyah & S. K. Elagan - 2022 - Complexity 2022:1-25.
    In this article, we investigated a deterministic model of pneumonia-meningitis coinfection. Employing the Atangana–Baleanu fractional derivative operator in the Caputo framework, we analyze a seven-component approach based on ordinary differential equations. Furthermore, the invariant domain, disease-free as well as endemic equilibria, and the validity of the model’s potential results are all investigated. According to controller design evaluation and modelling, the modulation technique devised is effective in diminishing the proportion of incidences in various compartments. A fundamental reproducing value is generated (...)
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  14.  20
    Numerical Simulation of a Class of Three-Dimensional Kolmogorov Model with Chaotic Dynamic Behavior by Using Barycentric Interpolation Collocation Method.Mingjing Du, Junmei Li, Yulan Wang & Wei Zhang - 2019 - Complexity 2019:1-14.
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  15.  24
    Numerically solving physiological models based on a polynomial approach.F. Tudoret, A. Bardou & G. Carrault - 2001 - Acta Biotheoretica 49 (4):247-260.
    Much research effort has been directed in different physiological contexts towards describing realistic behaviors with differential equations. One observes obviously that more state-variables give the model more accuracy. Unfortunately, the computational cost involved is higher. A new algorithm is presented for simulating a model described by a system of differential equations in which efficiency may not be altered by its size. In order to do this, the method is based on a polynomial description of the state-variables' evolution and on a (...)
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  16.  16
    A numerical study of the overlap probability distribution and its sample-to-sample fluctuations in a mean-field model.Giorgio Parisi & Federico Ricci-Tersenghi - 2012 - Philosophical Magazine 92 (1-3):341-352.
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  17.  21
    Application of a model for numerical response to a probability learning situation.Norman H. Anderson - 1969 - Journal of Experimental Psychology 80 (1):19.
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  18.  47
    Numerical Results for the Hubbard Model: Implications for the High Tc Pairing Mechanism. [REVIEW]Douglas J. Scalapino & S. R. White - 2001 - Foundations of Physics 31 (1):27-39.
    Numerical studies of the Hubbard model and its strong-coupling form, the t-J model, show evidence for antiferromagnetic, $d_{x^{\text{2}} - y^2 } $ -pairing and stripe correlations which remind one of phenomena seen in the layered cuprate materials. Here, we ask what these numerical results imply about various scenarios for the pairing mechanism.
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  19.  11
    The Planetary Theory of Ibn al-Shatir: Reduction of the Geometric Models to Numerical Tables.Fuad Abbud - 1962 - Isis 53 (4):492-499.
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  20.  10
    Phase field modelling of grain boundary motion driven by curvature and stored energy gradients. Part I: theory and numerical implementation.G. Abrivard, E. P. Busso, S. Forest & B. Appolaire - 2012 - Philosophical Magazine 92 (28-30):3618-3642.
  21.  8
    Euler’s Numerical Method on Fractional DSEK Model under ABC Derivative.Fareeha Sami Khan, M. Khalid, Omar Bazighifan & A. El-Mesady - 2022 - Complexity 2022:1-12.
    In this paper, DSEK model with fractional derivatives of the Atangana-Baleanu Caputo is proposed. This paper gives a brief overview of the ABC fractional derivative and its attributes. Fixed point theory has been used to establish the uniqueness and existence of solutions for the fractional DSEK model. According to this theory, we will define two operators based on Lipschitzian and prove that they are contraction mapping and relatively compact. Ulam-Hyers stability theorem is implemented to prove the fractional DSEK model’s stability (...)
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  22.  4
    Learning qualitative models from numerical data.Jure Žabkar, Martin Možina, Ivan Bratko & Janez Demšar - 2011 - Artificial Intelligence 175 (9-10):1604-1619.
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  23.  28
    Ricardo's Numerical Example Versus Ricardian Trade Model: a Comparison of Two Distinct Notions of Comparative Advantage.Jorge Morales Meoqui - 2017 - Economic Thought 6 (1):35.
    The so-called Ricardian trade model of contemporary economic textbooks is not a rational reconstruction of Ricardo's famous numerical example in chapter seven of the Principles. It differs from the latter in terms of the definition of the four numbers, relevant cost comparison, rule for specialisation, assumptions and theoretical implications. Thus, the widespread critique regarding the unrealistic assumptions of the textbook trade model does not apply to Ricardo's original proof of comparative advantage.
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  24.  26
    Asymmetric Switch Costs in Numeral Naming and Number Word Reading: Implications for Models of Bilingual Language Production.Michael G. Reynolds, Sophie Schlöffel & Francesca Peressotti - 2015 - Frontiers in Psychology 6.
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  25.  20
    Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation.Huiyuan Xiong, Xionglai Zhu & Ronghui Zhang - 2018 - Complexity 2018:1-14.
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  26. Models in the Geosciences.Alisa Bokulich & Naomi Oreskes - 2017 - In Magnani Lorenzo & Bertolotti Tommaso Wayne (eds.), Springer Handbook of Model-Based Science. Springer. pp. 891-911.
    The geosciences include a wide spectrum of disciplines ranging from paleontology to climate science, and involve studies of a vast range of spatial and temporal scales, from the deep-time history of microbial life to the future of a system no less immense and complex than the entire Earth. Modeling is thus a central and indispensable tool across the geosciences. Here, we review both the history and current state of model-based inquiry in the geosciences. Research in these fields makes use of (...)
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  27.  16
    Numerical Modeling and Investigation on Aerodynamic Noise Characteristics of Pantographs in High-Speed Trains.Xiaoqi Sun & Han Xiao - 2018 - Complexity 2018:1-12.
    Pantographs are important devices on high-speed trains. When a train runs at a high speed, concave and convex parts of the train cause serious airflow disturbances and result in flow separation, eddy shedding, and breakdown. A strong fluctuation pressure field will be caused and transformed into aerodynamic noises. When high-speed trains reach 300 km/h, aerodynamic noises become the main noise source. Aerodynamic noises of pantographs occupy a large proportion in far-field aerodynamic noises of the whole train. Therefore, the problem of (...)
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  28.  17
    Analysis of the Epidemic Biological Model of Tuberculosis (TB) via Numerical Schemes.S. Kanwal, M. K. Siddiqui, E. Bonyah, K. Sarwar, T. S. Shaikh & N. Ahmed - 2022 - Complexity 2022:1-13.
    Tuberculosis is caused by bacillus Mycobacterium tuberculosis. In this study, a mathematical model of tuberculosis is analyzed. The numerical behaviour of the considered model is analyzed including basic reproduction number and stability. We applied three numerical techniques to this model, i.e., nonstandard finite difference scheme, Runge–Kutta method of order 4, and forward Euler scheme. NSFD scheme preserves all the essential properties of the model. Acquired results corroborate that NSFD scheme converges for each step size. While the other two (...)
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  29.  69
    Bootstrapping in a language of thought: A formal model of numerical concept learning.Steven T. Piantadosi, Joshua B. Tenenbaum & Noah D. Goodman - 2012 - Cognition 123 (2):199-217.
  30.  17
    A Comparison of Finite Difference and Finite Volume Methods with Numerical Simulations: Burgers Equation Model.Ali Hasan Ali, Ahmed Shawki Jaber, Mustafa T. Yaseen, Mohammed Rasheed, Omer Bazighifan & Taher A. Nofal - 2022 - Complexity 2022:1-9.
    In this paper, we present an intensive investigation of the finite volume method compared to the finite difference methods. In order to show the main difference in the way of approaching the solution, we take the Burgers equation and the Buckley–Leverett equation as examples to simulate the previously mentioned methods. On the one hand, we simulate the results of the finite difference methods using the schemes of Lax–Friedrichs and Lax–Wendroff. On the other hand, we apply Godunov’s scheme to simulate the (...)
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  31.  22
    ADAPT: A Developmental, Asemantic, and Procedural Model for Transcoding From Verbal to Arabic Numerals.Pierre Barrouillet, Valérie Camos, Pierre Perruchet & Xavier Seron - 2004 - Psychological Review 111 (2):368-394.
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  32. Numerical simulations of the Lewis signaling game: Learning strategies, pooling equilibria, and the evolution of grammar.Jeffrey A. Barrett - unknown
    David Lewis (1969) introduced sender-receiver games as a way of investigating how meaningful language might evolve from initially random signals. In this report I investigate the conditions under which Lewis signaling games evolve to perfect signaling systems under various learning dynamics. While the 2-state/2- term Lewis signaling game with basic urn learning always approaches a signaling system, I will show that with more than two states suboptimal pooling equilibria can evolve. Inhomogeneous state distributions increase the likelihood of pooling equilibria, but (...)
     
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  33. Numerical origins: The critical questions.Karenleigh Anne Overmann - 2021 - Journal of Cognition and Culture 5 (21):449-468.
    Four perspectives on numerical origins are examined. The nativist model sees numbers as an aspect of numerosity, the biologically endowed ability to appreciate quantity that humans share with other species. The linguistic model sees numbers as a function of language. The embodied model sees numbers as conceptual metaphors informed by physical experience and expressed in language. Finally, the extended model sees numbers as conceptual outcomes of a cognitive system that includes material forms as constitutive components. If numerical origins (...)
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  34.  28
    Considering digits in a current model of numerical development.Stephanie Roesch & Korbinian Moeller - 2014 - Frontiers in Human Neuroscience 8.
  35.  9
    Numerical Study on Crack Distributions of the Single-Layer Building under Seismic Waves.Fenghui Dong, Zhipeng Zhong & Jin Cheng - 2018 - Complexity 2018:1-16.
    This paper conducts a numerical simulation of the antiseismic performance for single-layer masonry structures, completes a study on crack distributions and detailed characteristics of masonry structures, and finally verifies the correctness of the numerical model by experimental tests. This paper also provides a reinforced proposal to improve the antiseismic performance of single-layer masonry structures. Results prove that the original model suffers more serious damage than the reinforced model; in particular, longitudinal cracks appear on bottoms of two longitudinal walls (...)
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  36. From numerical concepts to concepts of number.Lance J. Rips, Amber Bloomfield & Jennifer Asmuth - 2008 - Behavioral and Brain Sciences 31 (6):623-642.
    Many experiments with infants suggest that they possess quantitative abilities, and many experimentalists believe that these abilities set the stage for later mathematics: natural numbers and arithmetic. However, the connection between these early and later skills is far from obvious. We evaluate two possible routes to mathematics and argue that neither is sufficient: (1) We first sketch what we think is the most likely model for infant abilities in this domain, and we examine proposals for extrapolating the natural number concept (...)
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  37.  35
    Numerical instability and dynamical systems.Vincent Ardourel & Julie Jebeile - 2021 - European Journal for Philosophy of Science 11 (2):1-21.
    In philosophical studies regarding mathematical models of dynamical systems, instability due to sensitive dependence on initial conditions, on the one side, and instability due to sensitive dependence on model structure, on the other, have by now been extensively discussed. Yet there is a third kind of instability, which by contrast has thus far been rather overlooked, that is also a challenge for model predictions about dynamical systems. This is the numerical instability due to the employment of numerical methods (...)
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  38. Numerical testing of evolution theories.Nils Aall Barricelli - 1962 - Acta Biotheoretica 16 (1):69-98.
    An interpretive system for the IBM 704 computer permitting interpretation of the genetic pattern of a numeric symbioorganism as a game strategy has been developed. Selection for best performance in a simple game has been applied in a preliminary experiment. An objective method to measure the quality of a game played is described. The results presented in the article show a small but significant improvement of game quality during a period of 2300 generations.The general characteristics of the phenomena observed are (...)
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  39. Considering digits in a current model of numerical development.Stephanie Roesch & Korbinian Moeller - 2016 - In Philippe Chassy & Wolfgang Grodd (eds.), Abstract mathematical cognition. [Lausanne, Switzerland]: Frontiers Media SA.
     
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  40.  8
    Domain-general and domain-specific influences on emerging numerical cognition: Contrasting uni-and bidirectional prediction models.I. Coolen, R. Merkley, D. Ansari, E. Dove, A. Dowker, A. Mills, V. Murphy, M. von Spreckelsen & G. Scerif - 2021 - Cognition 215 (C):104816.
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  41.  15
    Three-dimensional strain localization of water-saturated clay and numerical simulation using an elasto-viscoplastic model.Y. Higo, F. Oka, T. Kodaka & S. Kimoto - 2006 - Philosophical Magazine 86 (21-22):3205-3240.
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  42. Numerical Origins: The Critical Questions.Karenleigh A. Overmann - 2021 - Journal of Cognition and Culture 21 (5):449-468.
    Four perspectives on numerical origins are examined. The nativist model sees numbers as an aspect of numerosity, the biologically endowed ability to appreciate quantity that humans share with other species. The linguistic model sees numbers as a function of language. The embodied model sees numbers as conceptual metaphors informed by physical experience and expressed in language. Finally, the extended model sees numbers as conceptual outcomes of a cognitive system that includes material forms as constitutive components. If numerical origins (...)
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  43. Minimal models and canonical neural computations: the distinctness of computational explanation in neuroscience.M. Chirimuuta - 2014 - Synthese 191 (2):127-153.
    In a recent paper, Kaplan (Synthese 183:339–373, 2011) takes up the task of extending Craver’s (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in (...)
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  44. Functional Imaging Reveals Numerous Fields in the Monkey Auditory Cortex.Mark Augath - unknown
    Anatomical studies propose that the primate auditory cortex contains more fields than have actually been functionally confirmed or described. Spatially resolved functional magnetic resonance imaging (fMRI) with carefully designed acoustical stimulation could be ideally suited to extend our understanding of the processing within these fields. However, after numerous experiments in humans, many auditory fields remain poorly characterized. Imaging the macaque monkey is of particular interest as these species have a richer set of anatomical and neurophysiological data to clarify the source (...)
     
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  45. Modelling vagueness: what can we ignore?Rosanna Keefe - 2012 - Philosophical Studies 161 (3):453-470.
    A theory of vagueness gives a model of vague language and of reasoning within the language. Among the models that have been offered are Degree Theorists’ numerical models that assign values between 0 and 1 to sentences, rather than simply modelling sentences as true or false. In this paper, I ask whether we can benefit from employing a rich, well-understood numerical framework, while ignoring those aspects of it that impute a level of mathematical precision that is not (...)
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  46. Explanatory model of emotional-cognitive variables in school mathematics performance: a longitudinal study in primary school.Gamal Cerda, Carlos Pérez, José I. Navarro, Manuel Aguilar, José Antonio Casas & Estivaliz Aragon - 2015 - Frontiers in Psychology 6:146673.
    This study tested a structural model of cognitive-emotional explanatory variables to explain performance in mathematics. The predictor variables assessed were related to students’ level of development of early mathematical competencies (EMCs), specifically, relational and numerical competencies, predisposition toward mathematics, and the level of logical intelligence in a population of primary school Chilean students (n = 634). This longitudinal study also included the academic performance of the students during a period of four years as a variable. The sampled students were (...)
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  47. FBST Regularization and Model Selection.Julio Michael Stern & Carlos Alberto de Braganca Pereira - 2001 - In Julio Michael Stern & Carlos Alberto de Braganca Pereira (eds.), Annals of the 7th International Conference on Information Systems Analysis and Synthesis. Orlando FL: pp. 7: 60-65..
    We show how the Full Bayesian Significance Test (FBST) can be used as a model selection criterion. The FBST was presented by Pereira and Stern as a coherent Bayesian significance test. Key Words: Bayesian test; Evidence; Global optimization; Information; Model selection; Numerical integration; Posterior density; Precise hypothesis; Regularization. AMS: 62A15; 62F15; 62H15.
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  48. Models of recognition, repetition priming, and fluency: Exploring a new framework.Christopher J. Berry, David R. Shanks, Maarten Speekenbrink & Richard N. A. Henson - 2011 - Psychological Review 24.
    We present a new modeling framework for recognition memory and repetition priming based on signal detection theory. We use this framework to specify and test the predictions of 4 models: (a) a single-system (SS) model, in which one continuous memory signal drives recognition and priming; (b) a multiple-systems-1 (MS1) model, in which completely independent memory signals (such as explicit and implicit memory) drive recognition and priming; (c) a multiple-systems-2 (MS2) model, in which there are also 2 memory signals, but some (...)
     
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  49. Modeling ancient and modern arithmetic practices: Addition and multiplication with Arabic and Roman numerals.Dirk Schlimm & Hansjörg Neth - 2008 - In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 2097--2102.
    To analyze the task of mental arithmetic with external representations in different number systems we model algorithms for addition and multiplication with Arabic and Roman numerals. This demonstrates that Roman numerals are not only informationally equivalent to Arabic ones but also computationally similar—a claim that is widely disputed. An analysis of our models' elementary processing steps reveals intricate tradeoffs between problem representation, algorithm, and interactive resources. Our simulations allow for a more nuanced view of the received wisdom on Roman numerals. (...)
     
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  50. The role of epistemological models in Veronese's and Bettazzi's theory of magnitudes.Paola Cantù - 2010 - In M. D'Agostino, G. Giorello, F. Laudisa, T. Pievani & C. Sinigaglia (eds.), New Essays in Logic and Philosophy of Science. College Publications.
    The philosophy of mathematics has been accused of paying insufficient attention to mathematical practice: one way to cope with the problem, the one we will follow in this paper on extensive magnitudes, is to combine the `history of ideas' and the `philosophy of models' in a logical and epistemological perspective. The history of ideas allows the reconstruction of the theory of extensive magnitudes as a theory of ordered algebraic structures; the philosophy of models allows an investigation into the way epistemology (...)
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