Switch to: References

Citations of:

A tale of two methods

Synthese 169 (3):575 - 592 (2009)

Add citations

You must login to add citations.
  1. Interdisciplinarity in the Making: Models and Methods in Frontier Science.Nancy J. Nersessian - 2022 - Cambridge, MA: MIT.
    A cognitive ethnography of how bioengineering scientists create innovative modeling methods. In this first full-scale, long-term cognitive ethnography by a philosopher of science, Nancy J. Nersessian offers an account of how scientists at the interdisciplinary frontiers of bioengineering create novel problem-solving methods. Bioengineering scientists model complex dynamical biological systems using concepts, methods, materials, and other resources drawn primarily from engineering. They aim to understand these systems sufficiently to control or intervene in them. What Nersessian examines here is how cutting-edge bioengineering (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Using Computer Simulations for Hypothesis-Testing and Prediction: Epistemological Strategies.Tan Nguyen - manuscript
    This paper explores the epistemological challenges in using computer simulations for two distinct goals: explanation via hypothesis-testing and prediction. It argues that each goal requires different strategies for justifying inferences drawn from simulation results due to different practical and conceptual constraints. The paper identifies unique and shared strategies researchers employ to increase confidence in their inferences for each goal. For explanation via hypothesis-testing, researchers need to address the underdetermination, interpretability, and attribution challenges. In prediction, the emphasis is on the model's (...)
    Download  
     
    Export citation  
     
    Bookmark  
  • Scientific representation in practice: Models and creative similarity.Julia Sanchez-Dorado - 2019 - Dissertation,
    The thesis proposes an account of the means of scientific representation focused on similarity, or more specifically, on the notion of “creative similarity”. I first distinguish between two different questions regarding the problem of representation: the question about the constituents and the question about the means of representation (following Suárez 2003; van Fraassen 2008). I argue that, although similarity is not a good candidate for constituent of representation, it can satisfactorily answer the question about the means of representation if adequately (...)
    Download  
     
    Export citation  
     
    Bookmark  
  • Biological Control Variously Materialized: Modeling, Experimentation and Exploration in Multiple Media.Tarja Knuuttila & Andrea Loettgers - 2021 - Perspectives on Science 29 (4):468-492.
    This paper examines two parallel discussions of scientific modeling which have invoked experimentation in addressing the role of models in scientific inquiry. One side discusses the experimental character of models, whereas the other focuses on their exploratory uses. Although both relate modeling to experimentation, they do so differently. The former has considered the similarities and differences between models and experiments, addressing, in particular, the epistemic value of materiality. By contrast, the focus on exploratory modeling has highlighted the various kinds of (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • From Implausible Artificial Neurons to Idealized Cognitive Models: Rebooting Philosophy of Artificial Intelligence.Catherine Stinson - 2020 - Philosophy of Science 87 (4):590-611.
    There is a vast literature within philosophy of mind that focuses on artificial intelligence, but hardly mentions methodological questions. There is also a growing body of work in philosophy of science about modeling methodology that hardly mentions examples from cognitive science. Here these discussions are connected. Insights developed in the philosophy of science literature about the importance of idealization provide a way of understanding the neural implausibility of connectionist networks. Insights from neurocognitive science illuminate how relevant similarities between models and (...)
    Download  
     
    Export citation  
     
    Bookmark   9 citations  
  • Why experiments matter.Arnon Levy & Adrian Currie - 2019 - Inquiry: An Interdisciplinary Journal of Philosophy 62 (9-10):1066-1090.
    ABSTRACTExperimentation is traditionally considered a privileged means of confirmation. However, why and how experiments form a better confirmatory source relative to other strategies is unclear, and recent discussions have identified experiments with various modeling strategies on the one hand, and with ‘natural’ experiments on the other hand. We argue that experiments aiming to test theories are best understood as controlled investigations of specimens. ‘Control’ involves repeated, fine-grained causal manipulation of focal properties. This capacity generates rich knowledge of the object investigated. (...)
    Download  
     
    Export citation  
     
    Bookmark   13 citations  
  • The epistemic superiority of experiment to simulation.Sherrilyn Roush - 2018 - Synthese 195 (11):4883-4906.
    This paper defends the naïve thesis that the method of experiment has per se an epistemic superiority over the method of computer simulation, a view that has been rejected by some philosophers writing about simulation, and whose grounds have been hard to pin down by its defenders. I further argue that this superiority does not come from the experiment’s object being materially similar to the target in the world that the investigator is trying to learn about, as both sides of (...)
    Download  
     
    Export citation  
     
    Bookmark   9 citations  
  • Computer Simulations in Science and Engineering. Concept, Practices, Perspectives.Juan Manuel Durán - 2018 - Springer.
    This book addresses key conceptual issues relating to the modern scientific and engineering use of computer simulations. It analyses a broad set of questions, from the nature of computer simulations to their epistemological power, including the many scientific, social and ethics implications of using computer simulations. The book is written in an easily accessible narrative, one that weaves together philosophical questions and scientific technicalities. It will thus appeal equally to all academic scientists, engineers, and researchers in industry interested in questions (...)
    Download  
     
    Export citation  
     
    Bookmark   22 citations  
  • Microbes, mathematics, and models.Maureen A. O'Malley & Emily C. Parke - 2018 - Studies in History and Philosophy of Science Part A 72:1-10.
    Microbial model systems have a long history of fruitful use in fields that include evolution and ecology. In order to develop further insight into modelling practice, we examine how the competitive exclusion and coexistence of competing species have been modelled mathematically and materially over the course of a long research history. In particular, we investigate how microbial models of these dynamics interact with mathematical or computational models of the same phenomena. Our cases illuminate the ways in which microbial systems and (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • Models on the move: Migration and imperialism.Seamus Bradley & Karim P. Y. Thébault - 2019 - Studies in History and Philosophy of Science Part A 77:81-92.
    We introduce ‘model migration’ as a species of cross-disciplinary knowledge transfer whereby the representational function of a model is radically changed to allow application to a new disciplinary context. Controversies and confusions that often derive from this phenomenon will be illustrated in the context of econophysics and phylogeographic linguistics. Migration can be usefully contrasted with concept of ‘imperialism’, that has been influentially discussed in the context of geographical economics. In particular, imperialism, unlike migration, relies upon extension of the original model (...)
    Download  
     
    Export citation  
     
    Bookmark   9 citations  
  • The epistemic superiority of experiment to simulation.Sherrilyn Roush - 2018 - Synthese 195 (11):4883-4906.
    This paper defends the naïve thesis that the method of experiment has per se an epistemic superiority over the method of computer simulation, a view that has been rejected by some philosophers writing about simulation, and whose grounds have been hard to pin down by its defenders. I further argue that this superiority does not come from the experiment’s object being materially similar to the target in the world that the investigator is trying to learn about, as both sides of (...)
    Download  
     
    Export citation  
     
    Bookmark   9 citations  
  • Homepage Eckhart Arnold.Eckhart Arnold (ed.) - 2001 - Munich: Preprint.
    This is my personal homepage. Find my philosophical papers under "Philosophy".
    Download  
     
    Export citation  
     
    Bookmark  
  • When can a Computer Simulation act as Substitute for an Experiment? A Case-Study from Chemisty.Johannes Kästner & Eckhart Arnold - manuscript
    In this paper we investigate with a case study from chemistry under what conditions a simulation can serve as a surrogate for an experiment. The case-study concerns a simulation of H2-formation in outer space. We find that in this case the simulation can act as a surrogate for an experiment, because there exists comprehensive theoretical background knowledge in form of quantum mechanics about the range of phenomena to which the investigated process belongs and because any particular modelling assumptions as can (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • Tools for Evaluating the Consequences of Prior Knowledge, but no Experiments. On the Role of Computer Simulations in Science.Eckhart Arnold - manuscript
    There is an ongoing debate on whether or to what degree computer simulations can be likened to experiments. Many philosophers are sceptical whether a strict separation between the two categories is possible and deny that the materiality of experiments makes a difference (Morrison 2009, Parker 2009, Winsberg 2010). Some also like to describe computer simulations as a “third way” between experimental and theoretical research (Rohrlich 1990, Axelrod 2003, Kueppers/Lenhard 2005). In this article I defend the view that computer simulations are (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Models, measurement and computer simulation: the changing face of experimentation.Margaret Morrison - 2009 - Philosophical Studies 143 (1):33-57.
    The paper presents an argument for treating certain types of computer simulation as having the same epistemic status as experimental measurement. While this may seem a rather counterintuitive view it becomes less so when one looks carefully at the role that models play in experimental activity, particularly measurement. I begin by discussing how models function as “measuring instruments” and go on to examine the ways in which simulation can be said to constitute an experimental activity. By focussing on the connections (...)
    Download  
     
    Export citation  
     
    Bookmark   74 citations  
  • Explaining simulated phenomena. A defense of the epistemic power of computer simulations.Juan M. Durán - 2013 - Dissertation, University of Stuttgart
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • Experimental Modeling in Biology: In Vivo Representation and Stand-ins As Modeling Strategies.Marcel Weber - 2014 - Philosophy of Science 81 (5):756-769.
    Experimental modeling in biology involves the use of living organisms (not necessarily so-called "model organisms") in order to model or simulate biological processes. I argue here that experimental modeling is a bona fide form of scientific modeling that plays an epistemic role that is distinct from that of ordinary biological experiments. What distinguishes them from ordinary experiments is that they use what I call "in vivo representations" where one kind of causal process is used to stand in for a physically (...)
    Download  
     
    Export citation  
     
    Bookmark   15 citations  
  • Models and Simulations in the Historical Emergence of the Science of Complexity.Franck Varenne - 2009 - In Moulay Aziz-Alaoui & Cyrille Bertelle (eds.), From System Complexity to Emergent Properties. Springer. pp. 3--21.
    As brightly shown by Mainzer [24], the science of complexity has many distinct origins in many disciplines. Those various origins has led to “an interdisciplinary methodology to explain the emergence of certain macroscopic phenomena via the nonlinear interactions of microscopic elements” (ibid.). This paper suggests that the parallel and strong expansion of modeling and simulation - especially after the Second World War and the subsequent development of computers - is a rationale which also can be counted as an explanation of (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • When Experiments Need Models.Donal Khosrowi - 2021 - Philosophy of the Social Sciences 51 (4):400-424.
    This paper argues that an important type of experiment-target inference, extrapolating causal effects, requires models to be successful. Focusing on extrapolation in Evidence-Based Policy, it is ar...
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • 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 (...)
    Download  
     
    Export citation  
     
    Bookmark   15 citations  
  • Real moral problems in the use of virtual reality.Erick Jose Ramirez & Scott LaBarge - 2018 - Ethics and Information Technology (4):249-263.
    In this paper, we argue that, under a specific set of circumstances, designing and employing certain kinds of virtual reality (VR) experiences can be unethical. After a general discussion of simulations and their ethical context, we begin our argu-ment by distinguishing between the experiences generated by different media (text, film, computer game simulation, and VR simulation), and argue that VR experiences offer an unprecedented degree of what we call “perspectival fidelity” that prior modes of simulation lack. Additionally, we argue that (...)
    Download  
     
    Export citation  
     
    Bookmark   13 citations  
  • Robot life: simulation and participation in the study of evolution and social behavior.Christopher M. Kelty - 2018 - History and Philosophy of the Life Sciences 40 (1):16.
    This paper explores the case of using robots to simulate evolution, in particular the case of Hamilton’s Law. The uses of robots raises several questions that this paper seeks to address. The first concerns the role of the robots in biological research: do they simulate something or do they participate in something? The second question concerns the physicality of the robots: what difference does embodiment make to the role of the robot in these experiments. Thirdly, how do life, embodiment and (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • The argument from surprise.Adrian Currie - 2018 - Canadian Journal of Philosophy 48 (5):639-661.
    I develop an account of productive surprise as an epistemic virtue of scientific investigations which does not turn on psychology alone. On my account, a scientific investigation is potentially productively surprising when results can conflict with epistemic expectations, those expectations pertain to a wide set of subjects. I argue that there are two sources of such surprise in science. One source, often identified with experiments, involves bringing our theoretical ideas in contact with new empirical observations. Another, often identified with simulations, (...)
    Download  
     
    Export citation  
     
    Bookmark   14 citations  
  • 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 (...)
    Download  
     
    Export citation  
     
    Bookmark   31 citations  
  • Cultures of simulations vs. cultures of calculations? The development of simulation practices in meteorology and astrophysics.Mikaela Sundberg - 2010 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (3):273-281.
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  • Modeling and experimenting: The combinatorial strategy in synthetic biology.Tarja Knuuttila & Andrea Loettgers - unknown
    In which respects do modeling and experimenting resemble or differ from each other? We explore this question through studying in detail the combinatorial strategy in synthetic biology whereby scientists triangulate experimentation on model organisms, mathematical modeling, and synthetic modeling. We argue that this combinatorial strategy is due to the characteristic constraints of the three epistemic activities. Moreover, our case study shows that in some cases materiality clearly matters, in fact it provides the very rationale of synthetic modeling. We will show (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • Computer simulations and experiments: in vivo–in vitro conditions in biochemistry.Pio Garcia - 2015 - Foundations of Chemistry 17 (1):49-65.
    Scientific practices have been changed by the increasing use of computer simulations. A central question for philosophers is how to characterize computer simulations. In this paper, we address this question by analyzing simulations in biochemistry. We propose that simulations have been used in biochemistry long before computers arrived. Simulation can be described as a surrogate relationship between models. Moreover, a simulative aspect is implicit in the classical dichotomy between in vivo–in vitro conditions. Based on a discussion about how to characterize (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Computer Simulations in Science.Eric Winsberg - forthcoming - Stanford Encyclopedia of Philosophy.
    Download  
     
    Export citation  
     
    Bookmark   36 citations  
  • Chains of Reference in Computer Simulations.Franck Varenne - 2013 - FMSH Working Papers 51:1-32.
    This paper proposes an extensionalist analysis of computer simulations (CSs). It puts the emphasis not on languages nor on models, but on symbols, on their extensions, and on their various ways of referring. It shows that chains of reference of symbols in CSs are multiple and of different kinds. As they are distinct and diverse, these chains enable different kinds of remoteness of reference and different kinds of validation for CSs. Although some methodological papers have already underlined the role of (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • Scientific models, simulation, and the experimenter's regress.Axel Gelfert - 2011 - In Paul Humphreys & Cyrille Imbert (eds.), Models, Simulations, and Representations. New York: Routledge.
    According to the "experimenter's regress", disputes about the validity of experimental results cannot be closed by objective facts because no conclusive criteria other than the outcome of the experiment itself exist for deciding whether the experimental apparatus was functioning properly or not. Given the frequent characterization of simulations as "computer experiments", one might worry that an analogous regress arises for computer simulations. The present paper analyzes the most likely scenarios where one might expect such a "simulationist's regress" to surface, and, (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • Cultures of simulations vs. cultures of calculations? The development of simulation practices in meteorology and astrophysics.Mikaela Sundberg - 2010 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (3):273-281.
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  • Computer simulation and the philosophy of science.Eric Winsberg - 2009 - Philosophy Compass 4 (5):835-845.
    There are a variety of topics in the philosophy of science that need to be rethought, in varying degrees, after one pays careful attention to the ways in which computer simulations are used in the sciences. There are a number of conceptual issues internal to the practice of computer simulation that can benefit from the attention of philosophers. This essay surveys some of the recent literature on simulation from the perspective of the philosophy of science and argues that philosophers have (...)
    Download  
     
    Export citation  
     
    Bookmark   29 citations  
  • Regimes of Evidence in Complexity Sciences.Fabrizio Li Vigni - 2021 - Perspectives on Science 29 (1):62-103.
    Since their inception in the 1980s, complexity sciences have been described as a revolutionary new domain of research. By describing some of the practices and assumptions of its representatives, the present article shows that this field is an association of subdisciplines laying on existing disciplinary footholds. The general question guiding us here is: On what basis do complexity scientists consider their inquiry methods and results as valuable? To answer it, I describe five “epistemic argumentative regimes,” namely the ways in which (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • A Formal Framework for Computer Simulations: Surveying the Historical Record and Finding Their Philosophical Roots.Juan M. Durán - 2019 - Philosophy and Technology 34 (1):105-127.
    A chronicled approach to the notion of computer simulations shows that there are two predominant interpretations in the specialized literature. According to the first interpretation, computer simulations are techniques for finding the set of solutions to a mathematical model. I call this first interpretation the problem-solving technique viewpoint. In its second interpretation, computer simulations are considered to describe patterns of behavior of a target system. I call this second interpretation the description of patterns of behavior viewpoint of computer simulations. This (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • How to infer explanations from computer simulations.Florian J. Boge - 2020 - Studies in History and Philosophy of Science Part A 82:25-33.
    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 (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • Confirmation based on analogical inference: Bayes meets Jeffrey.Christian J. Feldbacher-Escamilla & Alexander Gebharter - 2020 - Canadian Journal of Philosophy 50 (2):174-194.
    Certain hypotheses cannot be directly confirmed for theoretical, practical, or moral reasons. For some of these hypotheses, however, there might be a workaround: confirmation based on analogical reasoning. In this paper we take up Dardashti, Hartmann, Thébault, and Winsberg’s (in press) idea of analyzing confirmation based on analogical inference Baysian style. We identify three types of confirmation by analogy and show that Dardashti et al.’s approach can cover two of them. We then highlight possible problems with their model as a (...)
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  • Thought Experiments and Simulation Experiments: Exploring Hypothetical Worlds.Johannes Lenhard - unknown
    Both thought experiments and simulation experiments apparently belong to the family of experiments, though they are somewhat special members because they work without intervention into the natural world. Instead they explore hypothetical worlds. For this reason many have wondered whether referring to them as “experiments” is justified at all. While most authors are concerned with only one type of “imagined” experiment – either simulation or thought experiment – the present chapter hopes to gain new insight by considering what the two (...)
    Download  
     
    Export citation  
     
    Bookmark   8 citations  
  • Michael Ruse, The Gaïa hypothesis: science on a pagan planet: University of Chicago Press, Chicago, 2013, 272 pp, $26.00. [REVIEW]Sébastien Dutreuil - 2014 - History and Philosophy of the Life Sciences 36 (1):149-151.
    This article on the epistemology of computational models stems from an analysis of the Gaïa hypothesis. It begins with James Kirchner’s criticisms of the central computational model of GH: Daisyworld. Among other things, the model has been criticized for being too abstract, describing fictional entities and trying to answer counterfactual questions. For these reasons the model has been considered not testable and therefore not legitimate in science, and in any case not very interesting since it explores non actual issues. This (...)
    Download  
     
    Export citation  
     
    Bookmark  
  • Mutant mice: Experimental organisms as materialised models in biomedicine.Lara Huber & Lara K. Keuck - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (3):385-391.
    Animal models have received particular attention as key examples of material models. In this paper, we argue that the specificities of establishing animal models—acknowledging their status as living beings and as epistemological tools—necessitate a more complex account of animal models as materialised models. This becomes particularly evident in animal-based models of diseases that only occur in humans: in these cases, the representational relation between animal model and human patient needs to be generated and validated. The first part of this paper (...)
    Download  
     
    Export citation  
     
    Bookmark   11 citations  
  • Is Simulation an Epistemic Substitute for Experimentation?Isabelle Peschard - unknown
    It is sometimes said that simulation can serve as epistemic substitute for experimentation. Such a claim might be suggested by the fast-spreading use of computer simulation to investigate phenomena not accessible to experimentation. But what does that mean? The paper starts with a clarification of the terms of the issue and then focuses on two powerful arguments for the view that simulation and experimentation are ‘epistemically on a par’. One is based on the claim that, in experimentation, no less than (...)
    Download  
     
    Export citation  
     
    Bookmark   7 citations  
  • Computer simulations and experiments: The case of the Higgs boson.Michela Massimi & Wahid Bhimji - 2015 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 51 (C):71-81.
    Download  
     
    Export citation  
     
    Bookmark   19 citations  
  • Standing on the Shoulders of Giants—And Then Looking the Other Way? Epistemic Opacity, Immersion, and Modeling in Hydraulic Engineering.Matthijs Kouw - 2016 - Perspectives on Science 24 (2):206-227.
    Over the course of the twentieth century, hydraulic engineering has come to rely primarily on the use of computational models. Disco and van den Ende hint towards the reasons for widespread adoption of computational models by pointing out that such models fulfill a crucial role as management tools in Dutch water management, and meet a more general desire to quantify water-related phenomena. The successful application of computational models implies blackboxing : “[w]hen a machine runs efficiently … one need focus only (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • About the warrants of computer-based empirical knowledge.Anouk Barberousse & Marion Vorms - 2014 - Synthese 191 (15):3595-3620.
    Computer simulations are widely used in current scientific practice, as a tool to obtain information about various phenomena. Scientists accordingly rely on the outputs of computer simulations to make statements about the empirical world. In that sense, simulations seem to enable scientists to acquire empirical knowledge. The aim of this paper is to assess whether computer simulations actually allow for the production of empirical knowledge, and how. It provides an epistemological analysis of present-day empirical science, to which the traditional epistemological (...)
    Download  
     
    Export citation  
     
    Bookmark   13 citations  
  • How simulations fail.Patrick Grim, Robert Rosenberger, Adam Rosenfeld, Brian Anderson & Robb E. Eason - 2011 - Synthese 190 (12):2367-2390.
    ‘The problem with simulations is that they are doomed to succeed.’ So runs a common criticism of simulations—that they can be used to ‘prove’ anything and are thus of little or no scientific value. While this particular objection represents a minority view, especially among those who work with simulations in a scientific context, it raises a difficult question: what standards should we use to differentiate a simulation that fails from one that succeeds? In this paper we build on a structural (...)
    Download  
     
    Export citation  
     
    Bookmark   14 citations  
  • Understanding and misunderstanding computer simulation: The case of atmospheric and climate science—An introduction.Matthias Heymann - 2010 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (3):193-200.
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • Computer Simulation, Experiment, and Novelty.Julie Jebeile - 2017 - International Studies in the Philosophy of Science 31 (4):379-395.
    It is often said that computer simulations generate new knowledge about the empirical world in the same way experiments do. My aim is to make sense of such a claim. I first show that the similarities between computer simulations and experiments do not allow them to generate new knowledge but invite the simulationist to interact with simulations in an experimental manner. I contend that, nevertheless, computer simulations and experiments yield new knowledge under the same epistemic circumstances, independently of any features (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • Are computer simulations experiments? And if not, how are they related to each other?Claus Beisbart - 2018 - European Journal for Philosophy of Science 8 (2):171-204.
    Computer simulations and experiments share many important features. One way of explaining the similarities is to say that computer simulations just are experiments. This claim is quite popular in the literature. The aim of this paper is to argue against the claim and to develop an alternative explanation of why computer simulations resemble experiments. To this purpose, experiment is characterized in terms of an intervention on a system and of the observation of the reaction. Thus, if computer simulations are experiments, (...)
    Download  
     
    Export citation  
     
    Bookmark   16 citations  
  • From data to phenomena and back again: computer-simulated signatures.Eran Tal - 2011 - Synthese 182 (1):117-129.
    This paper draws attention to an increasingly common method of using computer simulations to establish evidential standards in physics. By simulating an actual detection procedure on a computer, physicists produce patterns of data (‘signatures’) that are expected to be observed if a sought-after phenomenon is present. Claims to detect the phenomenon are evaluated by comparing such simulated signatures with actual data. Here I provide a justification for this practice by showing how computer simulations establish the reliability of detection procedures. I (...)
    Download  
     
    Export citation  
     
    Bookmark   9 citations  
  • Method-Driven Experiments and the Search for Dark Matter.Siska De Baerdemaeker - 2021 - Philosophy of Science 88 (1):124-144.
    Since the discovery of dark matter in the 1980s, multiple experiments have been set up to detect dark matter particles through some other mode than gravity. Particle physicists provide detailed jus...
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • On the Limits of Experimental Knowledge.Peter Evans & Karim P. Y. Thebault - 2020 - Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378 (2177).
    To demarcate the limits of experimental knowledge, we probe the limits of what might be called an experiment. By appeal to examples of scientific practice from astrophysics and analogue gravity, we demonstrate that the reliability of knowledge regarding certain phenomena gained from an experiment is not circumscribed by the manipulability or accessibility of the target phenomena. Rather, the limits of experimental knowledge are set by the extent to which strategies for what we call ‘inductive triangulation’ are available: that is, the (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations