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  1. Social Epistemology and Validation in Agent-Based Social Simulation.David Anzola - 2021 - Philosophy and Technology 34 (4):1333-1361.
    The literature in agent-based social simulation suggests that a model is validated when it is shown to ‘successfully’, ‘adequately’ or ‘satisfactorily’ represent the target phenomenon. The notion of ‘successful’, ‘adequate’ or ‘satisfactory’ representation, however, is both underspecified and difficult to generalise, in part, because practitioners use a multiplicity of criteria to judge representation, some of which are not entirely dependent on the testing of a computational model during validation processes. This article argues that practitioners should address social epistemology to achieve (...)
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  • Why Designing Is Not Experimenting: Design Methods, Epistemic Praxis and Strategies of Knowledge Acquisition in Architecture.Sabine Ammon - 2017 - Philosophy and Technology 30 (4):495-520.
    Using the example of architecture, this article defends the thesis that designing should not be regarded as a kind of experimenting. This is in contrast to a widespread methodological claim that design processes are equivalent to experimentation processes. The contrary thesis can be proven by focusing on actual practices, techniques and design strategies. Closely connected with the thesis is an even more important epistemological claim, which contends that designing serves not only to develop artefacts but is also a means of (...)
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  • Steering Representations—Towards a Critical Understanding of Digital Twins.Paulan Korenhof, Vincent Blok & Sanneke Kloppenburg - 2021 - Philosophy and Technology 34 (4):1751-1773.
    Digital Twins are conceptualised in the academic technical discourse as real-time realistic digital representations of physical entities. Originating from product engineering, the Digital Twin quickly advanced into other fields, including the life sciences and earth sciences. Digital Twins are seen by the tech sector as the new promising tool for efficiency and optimisation, while governmental agencies see it as a fruitful means for improving decision-making to meet sustainability goals. A striking example of the latter is the European Commission who wishes (...)
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  • Analogue Quantum Simulation: A Philosophical Prospectus.Dominik Hangleiter, Jacques Carolan & Karim P. Y. Thebault - unknown
    This paper provides the first systematic philosophical analysis of an increasingly important part of modern scientific practice: analogue quantum simulation. We introduce the distinction between `simulation' and `emulation' as applied in the context of two case studies. Based upon this distinction, and building upon ideas from the recent philosophical literature on scientific understanding, we provide a normative framework to isolate and support the goals of scientists undertaking analogue quantum simulation and emulation. We expect our framework to be useful to both (...)
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  • Trustworthy Simulations and Their Epistemic Hierarchy.Peter Mättig - 2021 - Synthese 199 (5-6):14427-14458.
    We analyze the usage of computer simulation at the LHC and derive seven jointly necessary requirements for a simulation to be considered ’trustworthy’, such that it can be used as proxy for experiments. We show that these requirements can also be applied to systems without direct experimental access and discuss their validity for properties that have not yet been probed. While being necessary, these requirements are not sufficient. Such trustworthy simulations will be analyzed for the relative epistemic statuses of simulation (...)
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  • Explaining Epistemic Opacity.Ramón Alvarado - unknown
    Conventional accounts of epistemic opacity, particularly those that stem from the definitive work of Paul Humphreys, typically point to limitations on the part of epistemic agents to account for the distinct ways in which systems, such as computational methods and devices, are opaque. They point, for example, to the lack of technical skill on the part of an agent, the failure to meet standards of best practice, or even the nature of an agent as reasons why epistemically relevant elements of (...)
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  • Degrees of Epistemic Opacity.Iñaki San Pedro - manuscript
    The paper analyses in some depth the distinction by Paul Humphreys between "epistemic opacity" —which I refer to as "weak epistemic opacity" here— and "essential epistemic opacity", and defends the idea that epistemic opacity in general can be made sense as coming in degrees. The idea of degrees of epistemic opacity is then exploited to show, in the context of computer simulations, the tight relation between the concept of epistemic opacity and actual scientific (modelling and simulation) practices. As a consequence, (...)
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  • Homepage Eckhart Arnold.Eckhart Arnold (ed.) - 2001 - Munich: Preprint.
    This is my personal homepage. Find my philosophical papers under "Philosophy".
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  • Why Simpler Computer Simulation Models Can Be Epistemically Better for Informing Decisions.Casey Helgeson, Vivek Srikrishnan, Klaus Keller & Nancy Tuana - 2021 - Philosophy of Science 88 (2):213-233.
    For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many ti...
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  • Humanistic Interpretation and Machine Learning.Juho Paakkonen & Petri Ylikoski - 2020 - Synthese 199 (1-2):1-37.
    This paper investigates how unsupervised machine learning methods might make hermeneutic interpretive text analysis more objective in the social sciences. Through a close examination of the uses of topic modeling—a popular unsupervised approach in the social sciences—it argues that the primary way in which unsupervised learning supports interpretation is by allowing interpreters to discover unanticipated information in larger and more diverse corpora and by improving the transparency of the interpretive process. This view highlights that unsupervised modeling does not eliminate the (...)
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  • Capturing the representational and the experimental in the modelling of artificial societies.David Anzola - 2021 - European Journal for Philosophy of Science 11 (3):1-29.
    Even though the philosophy of simulation is intended as a comprehensive reflection about the practice of computer simulation in contemporary science, its output has been disproportionately shaped by research on equation-based simulation in the physical and climate sciences. Hence, the particularities of alternative practices of computer simulation in other scientific domains are not sufficiently accounted for in the current philosophy of simulation literature. This article centres on agent-based social simulation, a relatively established type of simulation in the social sciences, to (...)
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  • 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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  • Epistemic Entitlements and the Practice of Computer Simulation.John Symons & Ramón Alvarado - 2019 - Minds and Machines 29 (1):37-60.
    What does it mean to trust the results of a computer simulation? This paper argues that trust in simulations should be grounded in empirical evidence, good engineering practice, and established theoretical principles. Without these constraints, computer simulation risks becoming little more than speculation. We argue against two prominent positions in the epistemology of computer simulation and defend a conservative view that emphasizes the difference between the norms governing scientific investigation and those governing ordinary epistemic practices.
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  • Thought Experiments in Biology.Guillaume Schlaepfer & Marcel Weber - 2018 - In Michael T. Stuart, Yiftach J. H. Fehige & James Robert Brown (eds.), The Routledge Companion to Thought Experiments. London: Routledge. pp. 243-256.
    Unlike in physics, the category of thought experiment is not very common in biology. At least there are no classic examples that are as important and as well-known as the most famous thought experiments in physics, such as Galileo’s, Maxwell’s or Einstein’s. The reasons for this are far from obvious; maybe it has to do with the fact that modern biology for the most part sees itself as a thoroughly empirical discipline that engages either in real natural history or in (...)
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  • Boon and Bane: On the Role of Adjustable Parameters in Simulation Models.Hans Hasse & Johannes Lenhard - 2017 - In Martin Carrier & Johannes Lenhard (eds.), Mathematics as a Tool. Springer Verlag.
    We claim that adjustable parameters play a crucial role in building and applying simulation models. We analyze that role and illustrate our findings using examples from equations of state in thermodynamics. In building simulation models, two types of experiments, namely, simulation and classical experiments, interact in a feedback loop, in which model parameters are adjusted. A critical discussion of how adjustable parameters function shows that they are boon and bane of simulation. They help to enlarge the scope of simulation far (...)
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  • Current Perspectives on the Development of the Philosophy of Informatics.Paweł Polak - 2017 - Philosophical Problems in Science 63:77-100.
    This article is an overview of the philosophy of informatics with a special regard to some Polish philosophers. It juxtaposes the informationistic worldview with the long-prevailing mechanical conceptualization of nature before introducing the metaphysical perspective of the information revolution in sciences. The article shows also how ontic pancomputationalism – regarded as an update to structural realism – could enrich the philosophical research in some classical topics. The paper concludes with a discussion of the philosophy of Jan Salamucha, a philosopher from (...)
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  • Software engineering standards for epidemiological models.Jack K. Horner & John F. Symons - 2020 - History and Philosophy of the Life Sciences 42 (4):1-24.
    There are many tangled normative and technical questions involved in evaluating the quality of software used in epidemiological simulations. In this paper we answer some of these questions and offer practical guidance to practitioners, funders, scientific journals, and consumers of epidemiological research. The heart of our paper is a case study of the Imperial College London covid-19 simulator, set in the context of recent work in epistemology of simulation and philosophy of epidemiology.
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  • Computer Modeling and Simulation: Increasing Reliability by Disentangling Verification and Validation.Vitaly Pronskikh - 2019 - Minds and Machines 29 (1):169-186.
    Verification and validation of computer codes and models used in simulations are two aspects of the scientific practice of high importance that recently have been discussed widely by philosophers of science. While verification is predominantly associated with the correctness of the way a model is represented by a computer code or algorithm, validation more often refers to the model’s relation to the real world and its intended use. Because complex simulations are generally opaque to a practitioner, the Duhem problem can (...)
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  • Reproducibility and the Concept of Numerical Solution.Johannes Lenhard & Uwe Küster - 2019 - Minds and Machines 29 (1):19-36.
    In this paper, we show that reproducibility is a severe problem that concerns simulation models. The reproducibility problem challenges the concept of numerical solution and hence the conception of what a simulation actually does. We provide an expanded picture of simulation that makes visible those steps of simulation modeling that are numerically relevant, but often escape notice in accounts of simulation. Examining these steps and analyzing a number of pertinent examples, we argue that numerical solutions are importantly different from usual (...)
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  • Gluing Life Together. Computer Simulation in the Life Sciences: An Introduction.Janina Wellmann - 2018 - History and Philosophy of the Life Sciences 40 (4):70.
    Over the course of the last three decades, computer simulations have become a major tool of doing science and engaging with the world, not least in an effort to predict and intervene in a future to come. Born in the context of the Second World War and the discipline of physics, simulations have long spread into most diverse fields of enquiry and technological application. This paper introduces a topical collection focussing on simulations in the life sciences. Echoing the current state (...)
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  • Climate Simulations: Uncertain Projections for an Uncertain World.Rafaela Hillerbrand - 2014 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 45 (1):17-32.
    Between the fourth and the recent fifth IPCC report, science as well as policy making have made great advances in dealing with uncertainties in global climate models. However, the uncertainties public decision making has to deal with go well beyond what is currently addressed by policy makers and climatologists alike. It is shown in this paper that within an anthropocentric framework, a whole hierarchy of models from various scientific disciplines is needed for political decisions as regards climate change. Via what (...)
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  • Models in the Geosciences.Alisa Bokulich & Naomi Oreskes - 2017 - In Lorenzo Magnani & Tommaso Wayne Bertolotti (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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  • Epistemic Issues in Computational Reproducibility: Software as the Elephant in the Room.Alexandre Hocquet & Frédéric Wieber - 2021 - European Journal for Philosophy of Science 11 (2):1-20.
    Computational reproducibility possesses its own dynamics and narratives of crisis. Alongside the difficulties of computing as an ubiquitous yet complex scientific activity, computational reproducibility suffers from a naive expectancy of total reproducibility and a moral imperative to embrace the principles of free software as a non-negotiable epistemic virtue. We argue that the epistemic issues at stake in actual practices of computational reproducibility are best unveiled by focusing on software as a pivotal concept, one that is surprisingly often overlooked in accounts (...)
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  • Proof of Concept Research.Steve Elliott - 2021 - Philosophy of Science 88 (2):258-280.
    Researchers often pursue proof of concept research, but criteria for evaluating such research remain poorly specified. This article proposes a general framework for proof of concept research that k...
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  • Computing as Empirical Science- Evolution as a Concept.Paweł Polak - 2016 - Studies in Logic, Grammar and Rhetoric 48 (1):49-69.
    This article presents the evolution of philosophical and methodological considerations concerning empiricism in computer/computing science. In this study, we trace the most important current events in the history of reflection on computing. The forerunners of Artificial Intelligence H.A. Simon and A. Newell in their paper Computer Science As Empirical Inquiry started these considerations. Later the concept of empirical computer science was developed by S.S. Shapiro, P. Wegner, A.H. Eden and P.J. Denning. They showed various empirical aspects of computing. This led (...)
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  • La valeur de l'incertitude : l'évaluation de la précision des mesures physiques et les limites de la connaissance expérimentale.Fabien Grégis - 2016 - Dissertation, Université Sorbonne Paris Cité Université Paris.Diderot (Paris 7)
    Abstract : A measurement result is never absolutely accurate: it is affected by an unknown “measurement error” which characterizes the discrepancy between the obtained value and the “true value” of the quantity intended to be measured. As a consequence, to be acceptable a measurement result cannot take the form of a unique numerical value, but has to be accompanied by an indication of its “measurement uncertainty”, which enunciates a state of doubt. What, though, is the value of measurement uncertainty? What (...)
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  • What Can Bouncing Oil Droplets Tell Us About Quantum Mechanics?Peter W. Evans & Karim P. Y. Thébault - 2020 - European Journal for Philosophy of Science 10 (3):1-32.
    A recent series of experiments have demonstrated that a classical fluid mechanical system, constituted by an oil droplet bouncing on a vibrating fluid surface, can be induced to display a number of behaviours previously considered to be distinctly quantum. To explain this correspondence it has been suggested that the fluid mechanical system provides a single-particle classical model of de Broglie’s idiosyncratic ‘double solution’ pilot wave theory of quantum mechanics. In this paper we assess the epistemic function of the bouncing oil (...)
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  • Why Build a Virtual Brain? Large-Scale Neural Simulations as Jump Start for Cognitive Computing.Matteo Colombo - 2016 - Journal of Experimental and Theoretical Artificial Intelligence.
    Despite the impressive amount of financial resources recently invested in carrying out large-scale brain simulations, it is controversial what the pay-offs are of pursuing this project. One idea is that from designing, building, and running a large-scale neural simulation, scientists acquire knowledge about the computational performance of the simulating system, rather than about the neurobiological system represented in the simulation. It has been claimed that this knowledge may usher in a new era of neuromorphic, cognitive computing systems. This study elucidates (...)
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  • Big Data – The New Science of Complexity.Wolfgang Pietsch - unknown
    Data-intensive techniques, now widely referred to as 'big data', allow for novel ways to address complexity in science. I assess their impact on the scientific method. First, big-data science is distinguished from other scientific uses of information technologies, in particular from computer simulations. Then, I sketch the complex and contextual nature of the laws established by data-intensive methods and relate them to a specific concept of causality, thereby dispelling the popular myth that big data is only concerned with correlations. The (...)
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  • Why Computer Simulations Are Not Inferences, and in What Sense They Are Experiments.Florian J. Boge - 2018 - European Journal for Philosophy of Science 9 (1):1-30.
    The question of where, between theory and experiment, computer simulations locate on the methodological map is one of the central questions in the epistemology of simulation. The two extremes on the map have them either be a kind of experiment in their own right, 317–329, 2005; Morrison Philosophical Studies, 143, 33–57, 2009; Morrison 2015; Massimi and Bhimji Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, 51, 71–81, 2015; Parker Synthese, 169, 483–496, (...)
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  • Stretching the Traditional Notion of Experiment in Computing: Explorative Experiments.Viola Schiaffonati - 2016 - Science and Engineering Ethics 22 (3):647-665.
    Experimentation represents today a ‘hot’ topic in computing. If experiments made with the support of computers, such as computer simulations, have received increasing attention from philosophers of science and technology, questions such as “what does it mean to do experiments in computer science and engineering and what are their benefits?” emerged only recently as central in the debate over the disciplinary status of the discipline. In this work we aim at showing, also by means of paradigmatic examples, how the traditional (...)
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