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  1. added 2020-04-20
    Polycratic Hierarchies and Networks: What Simulation-Modeling at the LHC Can Teach Us About the Epistemology of Simulation.Florian J. Boge & Christian Zeitnitz - forthcoming - Synthese:1-35.
    Large scale experiments at CERN’s Large Hadron Collider (LHC) rely heavily on computer simulations (CSs), a fact that has recently caught philosophers’ attention. CSs obviously require appropriate modeling, and it is a common assumption among philosophers that the relevant models can be ordered into hierarchical structures. Focusing on LHC’s ATLAS experiment, we will establish three central results here: (a) With some distinct modifications, individual components of ATLAS’ overall simulation infrastructure can be ordered into hierarchical structures. Hence, to a good degree (...)
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  2. added 2020-04-20
    How to Infer Explanations From Computer Simulations.Florian J. Boge - forthcoming - Studies in History and Philosophy of Science Part A.
    Computer simulations are involved in numerous branches of modern science, and science would not be the same without them. Yet the question of how they can explain real-world processes remains an issue of considerable debate. In this context, a range of authors have highlighted the inferences back to the world that computer simulations allow us to draw. I will first characterize the precise relation between computer and target of a simulation that allows us to draw such inferences. I then argue (...)
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  3. added 2020-02-10
    Expanding Theory Testing in General Relativity: LIGO and Parametrized Theories.Lydia Patton - forthcoming - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics.
    The multiple detections of gravitational waves by LIGO (the Laser Interferometer Gravitational-Wave Observatory), operated by Caltech and MIT, have been acclaimed as confirming Einstein's prediction, a century ago, that gravitational waves propagating as ripples in spacetime would be detected. Yunes and Pretorius (2009) investigate whether LIGO's template-based searches encode fundamental assumptions, especially the assumption that the background theory of general relativity is an accurate description of the phenomena detected in the search. They construct the parametrized post-Einsteinian (ppE) framework in response, (...)
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  4. added 2020-02-08
    Transparency in Complex Computational Systems.Kathleen A. Creel - forthcoming - Philosophy of Science.
    Scientists depend on complex computational systems that are often ineliminably opaque, to the detriment of our ability to give scientific explanations and detect artifacts. Some philosophers have suggested treating opaque systems instrumentally, but computer scientists developing strategies for increasing transparency are correct in finding this unsatisfying. Instead, I propose an analysis of transparency as having three forms: transparency of the algorithm, the realization of the algorithm in code, and the way that code is run on particular hardware and data. This (...)
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  5. added 2020-01-16
    What We Cannot Learn From Analogue Experiments.Karen Crowther, Niels S. Linnemann & Christian Wüthrich - 2019 - Synthese:1-26.
    Analogue experiments have attracted interest for their potential to shed light on inaccessible domains. For instance, ‘dumb holes’ in fluids and Bose–Einstein condensates, as analogues of black holes, have been promoted as means of confirming the existence of Hawking radiation in real black holes. We compare analogue experiments with other cases of experiment and simulation in physics. We argue—contra recent claims in the philosophical literature—that analogue experiments are not capable of confirming the existence of particular phenomena in inaccessible target systems. (...)
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  6. added 2019-12-31
    Exploring Minds: Modes of Modelling and Simulation in Artificial Intelligence.Hajo Greif - forthcoming - Perspectives on Science.
    The aim of this paper is to grasp the relevant distinctions between various ways in which models and simulations in Artificial Intelligence (AI) relate to cognitive phenomena. In order to get a systematic picture, a taxonomy is developed that is based on the coordinates of formal versus material analogies and theory-guided versus pre-theoretic models in science. These distinctions have parallels in the computational versus mimetic aspects and in analytic versus exploratory types of computer simulation. This taxonomy cuts across the traditional (...)
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  7. added 2019-12-09
    Simulation Models of the Evolution of Cooperation as Proofs of Logical Possibilities. How Useful Are They?Eckhart Arnold - 2013 - Etica E Politica 15 (2):101-138.
    This paper discusses critically what simulation models of the evolution ofcooperation can possibly prove by examining Axelrod’s “Evolution of Cooperation” and the modeling tradition it has inspired. Hardly any of the many simulation models of the evolution of cooperation in this tradition have been applicable empirically. Axelrod’s role model suggested a research design that seemingly allowed to draw general conclusions from simulation models even if the mechanisms that drive the simulation could not be identified empirically. But this research design was (...)
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  8. added 2019-12-09
    Computer Simulations and the Changing Face of Scientific Experimentation.Juan M. Durán & Eckhart Arnold (eds.) - 2013 - Cambridge Scholars Publishing.
    In this volume, scientists, historians, and philosophers join to examine computer simulations in scientific practice. One central aim of the volume is to provide a multiperspective view on the topic. Therefore, the text includes philosophical studies on computer simulations, as well as case studies from simulation practice, and historical studies of the evolution of simulations as a research method.
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  9. added 2019-12-09
    How Models Fail.Eckhart Arnold - 1st ed. 2015 - In Catrin Misselhorn (ed.), Collective Agency and Cooperation in Natural and Artificial Systems. Springer Verlag.
    Simulation models of the Reiterated Prisoner's Dilemma (in the following: RPD-models) are since 30 years considered as one of the standard tools to study the evolution of cooperation (Rangoni 2013; Hoffmann 2000). A considerable number of such simulation models has been produced by scientists. Unfortunately, though, none of these models has empirically been verified and there exists no example of empirical research where any of the RPD-models has successfully been employed to a particular instance of cooperation. Surprisingly, this has not (...)
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  10. added 2019-10-22
    Qualitative Models in Computational Simulative Sciences: Representation, Confirmation, Experimentation.Nicola Angius - 2019 - Minds and Machines 29 (3):397-416.
    The Epistemology Of Computer Simulation has developed as an epistemological and methodological analysis of simulative sciences using quantitative computational models to represent and predict empirical phenomena of interest. In this paper, Executable Cell Biology and Agent-Based Modelling are examined to show how one may take advantage of qualitative computational models to evaluate reachability properties of reactive systems. In contrast to the thesis, advanced by EOCS, that computational models are not adequate representations of the simulated empirical systems, it is shown how (...)
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  11. added 2019-09-25
    Towards a Taxonomy of the Model-Ladenness of Data.Alisa Bokulich - forthcoming - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association.
    Model-data symbiosis is the view that there is an interdependent and mutually beneficial relationship between data and models, whereby models are not only data-laden, but data are also model-laden or model filtered. In this paper I elaborate and defend the second, more controversial, component of the symbiosis view. In particular, I construct a preliminary taxonomy of the different ways in which theoretical and simulation models are used in the production of data sets. These include data conversion, data correction, data interpolation, (...)
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  12. added 2019-09-09
    Refounding of the Activity Concept? Towards a Federative Paradigm for Modeling and Simulation.Alexandre Muzy, Franck Varenne, Bernard P. Zeigler, Jonathan Caux, Patrick Coquillard, Luc Touraille, Dominique Prunetti, Philippe Caillou, Olivier Michel & David R. C. Hill - 2013 - Simulation - Transactions of the Society for Modeling and Simulation International 89 (2):156-177.
    Currently, the widely used notion of activity is increasingly present in computer science. However, because this notion is used in specific contexts, it becomes vague. Here, the notion of activity is scrutinized in various contexts and, accordingly, put in perspective. It is discussed through four scientific disciplines: computer science, biology, economics, and epistemology. The definition of activity usually used in simulation is extended to new qualitative and quantitative definitions. In computer science, biology and economics disciplines, the new simulation activity definition (...)
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  13. added 2019-09-09
    Quelques Aspects de L’Œuvre de Jean-Marie Legay.Franck Varenne - 2012 - Natures Sciences Sociétés 20 (4):461-463.
    Cet article revient sur la pratique scientifique et les thèses épistémologiques de Jean-Marie Legay concernant les modèles, les simulations et les systèmes complexes. Il montre qu'il y a une cohérence entre sa thèse anti-représentationnaliste concernant les modèles et les simulations et sa caractérisation même des systèmes complexes : une simulation informatique, seule, n'est pas une expérience au sens fort car, en l'isolant, on perd la dimension complexe de toute entreprise d'expérimentation scientifique dès lors qu'il y manque le modélisateur, le terrain (...)
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  14. added 2019-08-06
    Learning Through Simulation.Sara Aronowitz & Tania Lombrozo - 2020 - Philosophers' Imprint 20.
    Mental simulation — such as imagining tilting a glass to figure out the angle at which water would spill — can be a way of coming to know the answer to an internally or externally posed query. Is this form of learning a species of inference or a form of observation? We argue that it is neither: learning through simulation is a genuinely distinct form of learning. On our account, simulation can provide knowledge of the answer to a query even (...)
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  15. added 2019-07-03
    Why Simpler Computer Simulation Models Can Be Epistemically Better for Informing Decisions.Casey Helgeson, Vivek Srikrishnan, Klaus Keller & Nancy Tuana - forthcoming - Philosophy of Science.
    For computer simulation models to usefully inform climate risk management decisions, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many times over, and because computing resources are finite, uncertainty assessment is more feasible using models that need less computer processor time. Such models are generally simpler in the sense of being more idealized, or less realistic. So modelers face a trade-off between realism and extent of uncertainty quantification. Seeing this trade-off for the (...)
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  16. added 2019-06-29
    Validation of Computer Simulations From a Kuhnian Perspective.Eckhart Arnold - 2019 - In Claus Beisbart & Nicole J. Saam (eds.), Computer Simulation Validation - Fundamental Concepts, Methodological Frameworks, and Philosophical Perspectives. Heidelberg, Deutschland: Springer. pp. 203-224.
    While Thomas Kuhn's theory of scientific revolutions does not specifically deal with validation, the validation of simulations can be related in various ways to Kuhn's theory: 1) Computer simulations are sometimes depicted as located between experiments and theoretical reasoning, thus potentially blurring the line between theory and empirical research. Does this require a new kind of research logic that is different from the classical paradigm which clearly distinguishes between theory and empirical observation? I argue that this is not the case. (...)
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  17. added 2019-05-28
    Agent-Based Models and Simulations in Economics and Social Sciences: From Conceptual Exploration to Distinct Ways of Experimenting.Franck Varenne & Denis Phan - 2008 - In Nuno David, José Castro Caldas & Helder Coelho (eds.), Proceedings of the 3rd EPOS congress (Epistemological Perspectives On Simulations). Lisbon: pp. 51-69.
    Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological tools so as to show to what precise extent each author is right when he focuses on some empirical, instrumental or conceptual significance of his model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity, section 2 gives (...)
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  18. added 2019-05-13
    Compte rendu de L’observation scientifique, aspects philosophiques et pratiques de Vincent Israel-Jost. [REVIEW]Quentin Ruyant - 2018 - Lato Sensu, Revue de la Société de Philosophie des Sciences 5:41-43.
    Revue de l'ouvrage "l'observation scientifique" de Vincent Israël-Jost. -/- Review of the book "l'observation scientifique" of Vincent Israël-Jost.
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  19. added 2019-05-10
    Peeking Inside the Black Box: A New Kind of Scientific Visualization.Michael T. Stuart & Nancy J. Nersessian - 2018 - Minds and Machines 29 (1):87-107.
    Computational systems biologists create and manipulate computational models of biological systems, but they do not always have straightforward epistemic access to the content and behavioural profile of such models because of their length, coding idiosyncrasies, and formal complexity. This creates difficulties both for modellers in their research groups and for their bioscience collaborators who rely on these models. In this paper we introduce a new kind of visualization that was developed to address just this sort of epistemic opacity. The visualization (...)
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  20. added 2019-03-08
    The Termination Risks of Simulation Science.Preston Greene - 2020 - Erkenntnis 85 (2):489-509.
    Historically, the hypothesis that our world is a computer simulation has struck many as just another improbable-but-possible “skeptical hypothesis” about the nature of reality. Recently, however, the simulation hypothesis has received significant attention from philosophers, physicists, and the popular press. This is due to the discovery of an epistemic dependency: If we believe that our civilization will one day run many simulations concerning its ancestry, then we should believe that we are probably in an ancestor simulation right now. This essay (...)
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  21. added 2019-02-23
    Bachelard avec la simulation informatique: nous faut-il reconduire sa critique de l'intuition ?Franck Varenne - 2006 - In Robert Damien & B. Hufschmitt (eds.), Bachelard: Confiance Raisonnée Et Défiance Rationnelle. Besançon: Presses Universitaires de Franche-Comté. pp. 111-143.
    Dans un nombre croissant de domaines scientifiques - sciences de la nature, sciences humaines aussi bien que sciences des artefacts -, la simulation ne joue plus le rôle de succédané temporaire d'une théorie encore en gésine parce que non encore élaborée ; c'est-à-dire qu'elle ne joue plus systématiquement le rôle d'un modèle provisoire ou d'un schéma servant à condenser les mesures. C'est qu'elle n'a pas la nature d'un signe graphique, linguistique ou mathématique. Elle joue au contraire de plus en plus (...)
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  22. added 2019-01-28
    Learning About Reality Through Models and Computer Simulations.Melissa Jacquart - 2018 - Science & Education 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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  23. added 2018-12-02
    The Dark Side of the Force: When Computer Simulations Lead Us Astray and ``Model Think'' Narrows Our Imagination.Eckhart Arnold - manuscript
    This paper is intended as a critical examination of the question of when the use of computer simulations is beneficial to scientific explanations. This objective is pursued in two steps: First, I try to establish clear criteria that simulations must meet in order to be explanatory. Basically, a simulation has explanatory power only if it includes all causally relevant factors of a given empirical configuration and if the simulation delivers stable results within the measurement inaccuracies of the input parameters. If (...)
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  24. added 2018-10-21
    Computer Simulations in Science and Engineering. Concept, Practices, Perspectives.Juan Manuel Durán - 2018 - Springer.
  25. added 2018-09-08
    Epistemic Opacity, Confirmation Holism and Technical Debt: Computer Simulation in the Light of Empirical Software Engineering.Julian Newman - 2016 - In History and Philosophy of Computing (IFIP AICT 487). Cham, Switzerland: Springer. pp. 256-272.
    Epistemic opacity vis a vis human agents has been presented as an essential, ineliminable characteristic of computer simulation models resulting from the characteristics of the human cognitive agent. This paper argues, on the contrary, that such epistemic opacity as does occur in computer simulations is not a consequence of human limitations but of a failure on the part of model developers to adopt good software engineering practice for managing human error and ensuring the software artefact is maintainable. One consequence of (...)
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  26. 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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  27. 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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  28. added 2018-08-29
    Les notions de métaphore et d'analogie dans les épistémologies des modèles et des simulations.Franck Varenne - 2006 - Paris, France: Editions Petra.
    Le développement considérable des simulations informatiques dans les sciences contemporaines impose une remise à plat des épistémologies des modèles. Franck Varenne propose de revenir sur les limites des notions de métaphore et d'analogie pour penser les modèles, en particulier quand il s'agit des modèles composés, des pluri-modèles et des modèles de simulation (à objets ou à agents), tels qu'ils se développent depuis une dizaine d'années. Il suggère que le paradigme linguistique, à l'oeuvre aussi bien dans la pensée analytique anglo-saxonne que (...)
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  29. added 2018-08-28
    Models and Mechanisms in Network Neuroscience.Carlos Zednik - 2018 - Philosophical Psychology 32 (1):23-51.
    This paper considers the way mathematical and computational models are used in network neuroscience to deliver mechanistic explanations. Two case studies are considered: Recent work on klinotaxis by Caenorhabditis elegans, and a longstanding research effort on the network basis of schizophrenia in humans. These case studies illustrate the various ways in which network, simulation and dynamical models contribute to the aim of representing and understanding network mechanisms in the brain, and thus, of delivering mechanistic explanations. After outlining this mechanistic construal (...)
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  30. added 2018-08-28
    Théories et modèles en sciences humaines. Le cas de la géographie.Franck Varenne - 2017 - Paris, France: Editions Matériologiques.
    Face à la diversité et à la complexification des modes de formalisation, une épistémologie des méthodes scientifiques doit confronter directement ses analyses à une pluralité d’études de cas comparatives. C’est l’objectif de cet ouvrage. -/- Aussi, dans une première partie, propose-t-il d’abord une classification large et raisonnée des différentes fonctions de connaissance des théories, des modèles et des simulations (de fait, cette partie constitue un panorama d’épistémologie générale particulièrement poussé). C’est ensuite à la lumière de cette classification que les deux (...)
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  31. added 2018-08-28
    Théorie, Réalité, Modèle.Franck Varenne - 2012 - Paris, France: Editions Matériologiques.
    Dans cet ouvrage, Franck Varenne pose la question du réalisme scientifique, essentiellement dans sa forme contemporaine, et ce jusqu’aux années 1980. Il s’est donné pour cela la contrainte de focaliser l’attention sur ce que devenaient sa formulation et les réponses diverses qu’on a pu lui apporter en réaction spécifique à l’évolution parallèle qu’ont subie les notions de théories et surtout de modèles dans les sciences, à la même époque. Même si, bien sûr, on ne peut pas attribuer le considérable essor (...)
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  32. added 2018-08-19
    From Models to Simulations.Franck Varenne - 2018 - London, UK: Routledge.
    This book analyses the impact computerization has had on contemporary science and explains the origins, technical nature and epistemological consequences of the current decisive interplay between technology and science: an intertwining of formalism, computation, data acquisition, data and visualization and how these factors have led to the spread of simulation models since the 1950s. -/- Using historical, comparative and interpretative case studies from a range of disciplines, with a particular emphasis on the case of plant studies, the author shows how (...)
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  33. added 2018-06-16
    Combining Causal Bayes Nets and Cellular Automata: A Hybrid Modelling Approach to Mechanisms.Alexander Gebharter & Daniel Koch - 2018 - British Journal for the Philosophy of Science.
    Causal Bayes nets (CBNs) can be used to model causal relationships up to whole mechanisms. Though modelling mechanisms with CBNs comes with many advantages, CBNs might fail to adequately represent some biological mechanisms because—as Kaiser (2016) pointed out—they have problems with capturing relevant spatial and structural information. In this paper we propose a hybrid approach for modelling mechanisms that combines CBNs and cellular automata. Our approach can incorporate spatial and structural information while, at the same time, it comes with all (...)
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  34. added 2018-06-12
    Multiagent-Based Simulation in Biology.Francesco Amigoni & Viola Schiaffonati - 2007 - In L. Magnani & P. Li (eds.), Model-Based Reasoning in Science, Technology, and Medicine. Springer. pp. 179--191.
  35. added 2018-04-24
    Theoretical Technologies in an “Experimental” Setting: Empirical Modeling of Proteinic Objects and Simulation of Their Dynamics Within Scientific Collaborations Around a Supercomputer.Frederic Wieber - unknown
    This paper examines, as a case study, some modeling and simulating practices in protein chemistry. In this field, theorists try to grasp proteinic objects by constructing models of their structures and by simulating their dynamical properties. The kind of models they construct and the necessity of performing simulations are linked with the molecular complexity of proteins. Two main types of problems emerge from this complexity. First, experimental problems arise when scientists want to perform on (and to adapt to) proteins some (...)
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  36. added 2018-04-10
    The Nature of Computational Things.Franck Varenne - 2013 - In Frédéric Migayrou Brayer & Marie-Ange (eds.), Naturalizing Architecture. Orléans: HYX Editions. pp. 96-105.
    Architecture often relies on mathematical models, if only to anticipate the physical behavior of structures. Accordingly, mathematical modeling serves to find an optimal form given certain constraints, constraints themselves translated into a language which must be homogeneous to that of the model in order for resolution to be possible. Traditional modeling tied to design and architecture thus appears linked to a topdown vision of creation, of the modernist, voluntarist and uniformly normative type, because usually (mono)functionalist. One available instrument of calculation/representation/prescription (...)
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  37. added 2018-04-10
    Du Modèle à la Simulation Informatique.Franck Varenne - 2007 - Vrin.
    Avec l’évolution récente des modèles mathématiques vers des simulations informatiques, les formalisations du vivant sont de plus en plus intégratives, mixtes et, en un sens, réalistes. Plus généralement, les formalisations d’objets complexes deviennent assises sur et non plus seulement traitées par l’infrastructure informatique.Quelle est la véritable portée épistémologique de cette empirie simulée? Comment la distinguer de la créativité proprement interne aux mathématiques dont la philosophie des sciences a déjà su rendre compte?En se penchant sur les modèles de plantes, cette enquête (...)
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  38. added 2018-03-05
    Review of Sherry Turkle’s ‘Simulation and Its Discontents’. [REVIEW]Olle Blomberg - 2009 - Metapsychology Online Reviews 13 (47).
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  39. added 2018-01-08
    The Emergence of Symbol-Based Communication in a Complex System of Artificial Creatures.Angelo Loula, Ricardo Gudwin, Charbel El-Hani & João Queiroz - unknown
    We present here a digital scenario to simulate the emergence of self-organized symbol-based communication among artificial creatures inhabiting a virtual world of predatory events. In order to design the environment and creatures, we seek theoretical and empirical constraints from C.S.Peirce Semiotics and an ethological case study of communication among animals. Our results show that the creatures, assuming the role of sign users and learners, behave collectively as a complex system, where self-organization of communicative interactions plays a major role in the (...)
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  40. added 2018-01-06
    Simulation informatique et pluriformalisation des objets composites.Franck Varenne - 2009 - Philosophia Scientae 13:135-154.
    A recent evolution of computer simulations has led to the emergence of complex computer simulations. In particular, the need to formalize composite objects (those objects that are composed of other objects) has led to what the author suggests calling pluriformalizations, i.e. formalizations that are based on distinct sub-models which are expressed in a variety of heterogeneous symbolic languages. With the help of four case-studies, he shows that such pluriformalizations enable to formalize distinctly but simultaneously either different aspects or different parts (...)
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  41. added 2017-10-02
    Confirmation Via Analogue Simulation: What Dumb Holes Could Tell Us About Gravity.Radin Dardashti, Karim P. Y. Thébault & Eric Winsberg - 2017 - British Journal for the Philosophy of Science 68 (1).
    In this article we argue for the existence of ‘analogue simulation’ as a novel form of scientific inference with the potential to be confirmatory. This notion is distinct from the modes of analogical reasoning detailed in the literature, and draws inspiration from fluid dynamical ‘dumb hole’ analogues to gravitational black holes. For that case, which is considered in detail, we defend the claim that the phenomena of gravitational Hawking radiation could be confirmed in the case that its counterpart is detected (...)
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  42. added 2017-10-01
    BML Revisited: Statistical Physics, Computer Simulation, and Probability.Raissa M. D'Souza - 2006 - Complexity 12 (2):30-39.
  43. added 2017-09-21
    Computer Simulation, Measurement, and Data Assimilation.Wendy S. Parker - 2017 - British Journal for the Philosophy of Science 68 (1):273-304.
    This article explores some of the roles of computer simulation in measurement. A model-based view of measurement is adopted and three types of measurement—direct, derived, and complex—are distinguished. It is argued that while computer simulations on their own are not measurement processes, in principle they can be embedded in direct, derived, and complex measurement practices in such a way that simulation results constitute measurement outcomes. Atmospheric data assimilation is then considered as a case study. This practice, which involves combining information (...)
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  44. added 2017-06-14
    Imagination: A Sine Qua Non of Science.Michael T. Stuart - 2017 - Croatian Journal of Philosophy (49):9-32.
    What role does the imagination play in scientific progress? After examining several studies in cognitive science, I argue that one thing the imagination does is help to increase scientific understanding, which is itself indispensable for scientific progress. Then, I sketch a transcendental justification of the role of imagination in this process.
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  45. added 2016-12-08
    Does Matter Really Matter? Computer Simulations, Experiments, and Materiality.Wendy S. Parker - 2009 - Synthese 169 (3):483-496.
    A number of recent discussions comparing computer simulation and traditional experimentation have focused on the significance of “materiality.” I challenge several claims emerging from this work and suggest that computer simulation studies are material experiments in a straightforward sense. After discussing some of the implications of this material status for the epistemology of computer simulation, I consider the extent to which materiality (in a particular sense) is important when it comes to making justified inferences about target systems on the basis (...)
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  46. added 2016-12-08
    The Philosophy of Simulation: Hot New Issues or Same Old Stew?Roman Frigg & Julian Reiss - 2009 - Synthese 169 (3):593-613.
    Computer simulations are an exciting tool that plays important roles in many scientific disciplines. This has attracted the attention of a number of philosophers of science. The main tenor in this literature is that computer simulations not only constitute interesting and powerful new science , but that they also raise a host of new philosophical issues. The protagonists in this debate claim no less than that simulations call into question our philosophical understanding of scientific ontology, the epistemology and semantics of (...)
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  47. added 2016-12-08
    Social Explanation and Computational Simulation.R. Keith Sawyer - 2004 - Philosophical Explorations 7 (3):219-231.
    I explore a type of computational social simulation known as artificial societies. Artificial society simulations are dynamic models of real-world social phenomena. I explore the role that these simulations play in social explanation, by situating these simulations within contemporary philosophical work on explanation and on models. Many contemporary philosophers have argued that models provide causal explanations in science, and that models are necessary mediators between theory and data. I argue that artificial society simulations provide causal mechanistic explanations. I conclude that (...)
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  48. added 2016-12-05
    From Instructional Social Computer Simulation to Heidegger's Aesthetics.Ron Shiro Saito - 2000 - Dissertation, Indiana University
    Using Schon's conception of reflection-in-action as an organizing structure, the author examines instructional social computer simulation by designing and reflecting upon computer prototypes and linking this analysis to appropriate literature. ;The author begins his study by examining the theoretical antecedents of model and location simulations. However, eventually agreeing with Dilthey's critique that society cannot be represented via scientific, law-like generalizations, he decides that model/location simulation reflects the "standard view of science" approach to the representation of society. ;Drawing from the interpretivist (...)
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  49. added 2016-11-28
    Computer Simulation in the Physical Sciences.Fritz Rohrlich - 1990 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1990:507-518.
    Computer simulation is shown to be philosophically interesting because it introduces a qualitatively new methodology for theory construction in science different from the conventional two components of "theory" and "experiment and/or observation". This component is "experimentation with theoretical models." Two examples from the physical sciences are presented for the purpose of demonstration but it is claimed that the biological and social sciences permit similar theoretical model experiments. Furthermore, computer simulation permits theoretical models for the evolution of physical systems which use (...)
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  50. added 2016-11-04
    Computer Simulations, Idealizations and Approximations.Ronald Laymon - 1990 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1990:519 - 534.
    It's uncontroversial that notions of idealization and approximation are central to understanding computer simulations and their rationale. What's not so clear is what exactly these notions come to. Two distinct forms of approximation will be distinguished and their features contrasted with those of idealizations. These distinctions will be refined and closely tied to computer simulations by means of Scott-Strachey denotational programming semantics. The use of this sort of semantics also provides a convenient format for argumentation in favor of several theses (...)
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