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  1. added 2019-01-28
    Learning About Reality Through Models and Computer Simulations.Melissa Jacquart - 2018 - Science and Education: Academic Journal of Ushynsky University 27 (7-8):805-810.
    Margaret Morrison, (2015) Reconstructing Reality: Models, Mathematics, and Simulations. Oxford University Press, New York. -/- Scientific models, mathematical equations, and computer simulations are indispensable to scientific practice. Through the use of models, scientists are able to effectively learn about how the world works, and to discover new information. However, there is a challenge in understanding how scientists can generate knowledge from their use, stemming from the fact that models and computer simulations are necessarily incomplete representations, and partial descriptions, of their (...)
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  2. added 2018-11-12
    Idealizations and Understanding: Much Ado About Nothing?Emily Sullivan & Kareem Khalifa - forthcoming - Australasian Journal of Philosophy:1-17.
    Because idealizations frequently advance scientific understanding, many claim that falsehoods play an epistemic role. In this paper, we argue that these positions greatly overstate idealizations’ import for understanding. We introduce work on epistemic value to the debate surrounding idealizations and understanding, arguing that idealizations qua falsehoods only confer non-epistemic value to understanding. We argue for this claim by criticizing the leading accounts of how idealizations provide understanding. For each of these approaches, we show that: (a) idealizations’ false components only promote (...)
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  3. added 2018-10-28
    Stochastic Stability and Disagreements Between Dynamics.Aydin Mohseni - forthcoming - Philosophy of Science.
    The replicator dynamics and Moran process are the main deterministic and stochastic models of evolutionary game theory. These models are connected by a mean-field relationship—the former describes the expected behavior of the latter. However, there are conditions under which their predictions diverge. I demonstrate that the divergence between their predictions is a function of standard techniques used in their analysis, and of differences in the idealizations involved in each. My analysis reveals problems for stochastic stability analysis in a broad class (...)
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  4. added 2018-10-25
    The Exploratory Role of Idealizations and Limiting Cases in Models.Elay Shech & Axel Gelfert - forthcoming - Studia Metodologiczne.
    In this article we argue that idealizations and limiting cases in models play an exploratory role in science. Four senses of exploration are presented: exploration of the structure and representational capacities of theory; proof-of-principle demonstrations; potential explanations; and exploring the suitability of target systems. We illustrate our claims through three case studies, including the Aharonov-Bohm effect, the emergence of anyons and fractional quantum statistics, and the Hubbard model of the Mott phase transitions. We end by reflecting on how our case (...)
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  5. added 2018-09-04
    What Does a Computer Simulation Prove? The Case of Plant Modeling at CIRAD.Franck Varenne - 2001 - In N. Giambiasi & C. Frydman (eds.), Simulation in industry - ESS 2001, Proc. of the 13th European Simulation Symposium. Society for Computer Simulation (SCS).
    The credibility of digital computer simulations has always been a problem. Today, through the debate on verification and validation, it has become a key issue. I will review the existing theses on that question. I will show that, due to the role of epistemological beliefs in science, no general agreement can be found on this matter. Hence, the complexity of the construction of sciences must be acknowledged. I illustrate these claims with a recent historical example. Finally I temperate this diversity (...)
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  6. added 2018-08-29
    Modéliser le social. Méthodes fondatrices et évolutions récentes.Franck Varenne - 2011 - Paris, France: Dunod.
    Cet ouvrage très pédagogique informe les étudiants sur les méthodes quantitatives les plus classiques comme les plus récentes en sciences sociales, et notamment sur les différentes pratiques de modélisation et de simulation informatique des systèmes sociaux (sciences sociales computationnelles ou modèles informatiques).
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  7. added 2018-08-28
    Heuristics, Descriptions, and the Scope of Mechanistic Explanation.Carlos Zednik - 2015 - In P. Braillard & C. Malaterre (eds.), Explanation in Biology. An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Dordrecht: Springer. pp. 295-318.
    The philosophical conception of mechanistic explanation is grounded on a limited number of canonical examples. These examples provide an overly narrow view of contemporary scientific practice, because they do not reflect the extent to which the heuristic strategies and descriptive practices that contribute to mechanistic explanation have evolved beyond the well-known methods of decomposition, localization, and pictorial representation. Recent examples from evolutionary robotics and network approaches to biology and neuroscience demonstrate the increasingly important role played by computer simulations and mathematical (...)
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  8. added 2018-06-12
    Prisoner's Dilemma Doesn't Explain Much.Robert Northcott & Anna Alexandrova - 2015 - In Martin Peterson (ed.), The Prisoner’s Dilemma. Cambridge: Cambridge University Press. pp. 64-84.
    We make the case that the Prisoner’s Dilemma, notwithstanding its fame and the quantity of intellectual resources devoted to it, has largely failed to explain any phenomena of social scientific or biological interest. In the heart of the paper we examine in detail a famous purported example of Prisoner’s Dilemma empirical success, namely Axelrod’s analysis of WWI trench warfare, and argue that this success is greatly overstated. Further, we explain why this negative verdict is likely true generally and not just (...)
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  9. added 2018-04-27
    Simplified Models: A Different Perspective on Models as Mediators.C. D. McCoy & Michela Massimi - 2018 - European Journal for Philosophy of Science 8 (1):99-123.
    We introduce a novel point of view on the “models as mediators” framework in order to emphasize certain important epistemological questions about models in science which have so far been little investigated. To illustrate how this perspective can help answer these kinds of questions, we explore the use of simplified models in high energy physics research beyond the Standard Model. We show in detail how the construction of simplified models is grounded in the need to mitigate pressing epistemic problems concerning (...)
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  10. added 2018-03-29
    Research Habits in Financial Modelling: The Case of Non-Normativity of Market Returns in the 1970s and the 1980s.Boudewijn De Bruin & Christian Walter - 2017 - In Emiliano Ippoliti & Ping Chen (eds.), Methods and Finance: A Unifying View on Finance, Mathematics, and Philosophy. Cham: Springer. pp. 73-93.
    In this chapter, one considers finance at its very foundations, namely, at the place where assumptions are being made about the ways to measure the two key ingredients of finance: risk and return. It is well known that returns for a large class of assets display a number of stylized facts that cannot be squared with the traditional views of 1960s financial economics (normality and continuity assumptions, i.e. Brownian representation of market dynamics). Despite the empirical counterevidence, normality and continuity assumptions (...)
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  11. added 2018-02-17
    Modeling Social and Evolutionary Games.Angela Potochnik - 2012 - Studies in History and Philosophy of Science Part C 43 (1):202-208.
    When game theory was introduced to biology, the components of classic game theory models were replaced with elements more befitting evolutionary phenomena. The actions of intelligent agents are replaced by phenotypic traits; utility is replaced by fitness; rational deliberation is replaced by natural selection. In this paper, I argue that this classic conception of comprehensive reapplication is misleading, for it overemphasizes the discontinuity between human behavior and evolved traits. Explicitly considering the representational roles of evolutionary game theory brings to attention (...)
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  12. added 2017-12-12
    Idealized and Perspectival Representations: Some Reasons for Making a Distinction.Alexander Rueger - 2014 - Synthese 191 (8):1831-1845.
    I argue that an adequate understanding of the practice of constructing models in physics requires a distinction between two strategies that are commonly both labeled ‘idealization’. The formal characteristic of both methods is to let a parameter in the equations for a target system go to zero. But the discussion of examples from various applications of perturbation theory shows that there is in general a difference with respect to the aims such limiting procedures are supposed to serve; and with different (...)
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  13. added 2017-12-12
    The Aerodynamics of Insects: The Role of Models and Matter in Scientific Experimentation.Michelle R. Silva - 2005 - Social Epistemology 19 (4):325 – 337.
    Historians and philosophers of science have examined the relationship between language and practice for a long time. Scholars have made important contributions to the field by attending to the social, cultural and economic contexts in which scientific paradigms are created and re-created. However, this article posits that while it is true that scientific practice and the artifacts they generate are both socially and discursively constructed and therefore, inextricable from the human contexts that produce them, these artifacts are not only texts (...)
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  14. added 2017-12-12
    Komparative Aussagemuster in Bezug Zu Komplementären Und Enkaptischen Modellen der Morphologie.A. Ritterbusch - 1981 - Acta Biotheoretica 30 (1):49-66.
    The unity of organisms can be viewed in terms of the concepts of enkapsis and complementarity. A model (or a type) represents those properties (of elements, structure, and system) which renders cases - the organisms under consideration — comparable. Comparability is established by operations (or metamorphoses) which relate a case to a model. Therefore, the model and the operations must be enumerated together, if a certain morphology is to be established and applied. Two models, which in some way are related, (...)
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  15. added 2017-12-06
    A Theory of Scientific Model Construction: The Conceptual Process of Abstraction and Concretisation. [REVIEW]Demetris P. Portides - 2005 - Foundations of Science 10 (1):67-88.
    The process of abstraction and concretisation is a label used for an explicative theory of scientific model-construction. In scientific theorising this process enters at various levels. We could identify two principal levels of abstraction that are useful to our understanding of theory-application. The first level is that of selecting a small number of variables and parameters abstracted from the universe of discourse and used to characterise the general laws of a theory. In classical mechanics, for example, we select position and (...)
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  16. added 2017-11-27
    The Use of Models.Bruce Edmonds - manuscript
    The use of MABS (Multi-Agent Based Simulations) is analysed as the modelling of distributed (usually social) systems using MAS as the model structure. It is argued that rarely is direct modelling of target systems attempted but rather an abstraction of the target systems is modelled and insights gained about the abstraction then applied back to the target systems. The MABS modelling process is divided into six steps: abstraction, design, inference, analysis, interpretation and application. Some types of MABS papers are characterised (...)
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  17. added 2017-11-27
    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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  18. added 2017-11-27
    Bootstrapping Knowledge About Social Phenomena Using Simulation Models.Bruce Edmonds - unknown
    Formidable difficulties face anyone trying to model social phenomena using a formal system, such as a computer program. The differences between formal systems and complex, multi-facetted and meaning-laden social systems are so fundamental that many will criticise any attempt to bridge this gap. Despite this, there are those who are so bullish about the project of social simulation that they appear to believe that simple computer models, that are also useful and reliable indicators of how aspects of society works, are (...)
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  19. added 2017-11-01
    Partial Possible Models: An Approach to Interpret Students' Physical Representation.Fernando Flores Camacho & Leticia Gallegos Cazares - 1998 - Science Education 82 (1):15-29.