Results for 'computer simulations'

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  1. 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 (...)
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  2. Computer Simulation and the Features of Novel Empirical Data.Greg Lusk - 2016 - Studies in History and Philosophy of Science Part A 56:145-152.
    In an attempt to determine the epistemic status of computer simulation results, philosophers of science have recently explored the similarities and differences between computer simulations and experiments. One question that arises is whether and, if so, when, simulation results constitute novel empirical data. It is often supposed that computer simulation results could never be empirical or novel because simulations never interact with their targets, and cannot go beyond their programming. This paper argues against this position (...)
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  3. A Computer Simulation of the Argument From Disagreement.Johan E. Gustafsson & Martin Peterson - 2012 - Synthese 184 (3):387-405.
    In this paper we shed new light on the Argument from Disagreement by putting it to test in a computer simulation. According to this argument widespread and persistent disagreement on ethical issues indicates that our moral opinions are not influenced by any moral facts, either because no such facts exist or because they are epistemically inaccessible or inefficacious for some other reason. Our simulation shows that if our moral opinions were influenced at least a little bit by moral facts, (...)
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  4.  27
    Computer Simulation of Human Thinking: An Inquiry Into its Possibility and Implications.Napoleon Mabaquiao Jr - 2011 - Philosophia 40 (1):76-87.
    Critical in the computationalist account of the mind is the phenomenon called computational or computer simulation of human thinking, which is used to establish the theses that human thinking is a computational process and that computing machines are thinking systems. Accordingly, if human thinking can be simulated computationally then human thinking is a computational process; and if human thinking is a computational process then its computational simulation is itself a thinking process. This paper shows that the said phenomenon—the computational (...)
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  5. 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 (...)
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  6. 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 (...)
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  7. 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 (...)
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  8. 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 (...)
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  9. Varying the Explanatory Span: Scientific Explanation for Computer Simulations.Juan Manuel Durán - 2017 - International Studies in the Philosophy of Science 31 (1):27-45.
    This article aims to develop a new account of scientific explanation for computer simulations. To this end, two questions are answered: what is the explanatory relation for computer simulations? And what kind of epistemic gain should be expected? For several reasons tailored to the benefits and needs of computer simulations, these questions are better answered within the unificationist model of scientific explanation. Unlike previous efforts in the literature, I submit that the explanatory relation is (...)
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  10. Layers of Models in Computer Simulations.Thomas Boyer-Kassem - 2014 - International Studies in the Philosophy of Science 28 (4):417-436.
    I discuss here the definition of computer simulations, and more specifically the views of Humphreys, who considers that an object is simulated when a computer provides a solution to a computational model, which in turn represents the object of interest. I argue that Humphreys's concepts are not able to analyse fully successfully a case of contemporary simulation in physics, which is more complex than the examples considered so far in the philosophical literature. I therefore modify Humphreys's definition (...)
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  11.  44
    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 (...)
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  12.  11
    How Models Fail. A Critical Look at the History of Computer Simulations of the Evolution of Cooperation.Eckhart Arnold - 2015 - In Catrin Misselhorn (ed.), Collective Agency and Cooperation in Natural and Artificial Systems. Explanation, Implementation and Simulation, Philosophical Studies Series. Springer. pp. 261-279.
    Simulation models of the Reiterated Prisoner's Dilemma have been popular for studying the evolution of cooperation since more than 30 years now. However, there have been practically no successful instances of empirical application of any of these models. At the same time this lack of empirical testing and confirmation has almost entirely been ignored by the modelers community. In this paper, I examine some of the typical narratives and standard arguments with which these models are justified by their authors despite (...)
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  13. 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 and under what conditions 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 (...)
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  14. 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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  15. You Only Live Twice: A Computer Simulation of the Past Could Be Used for Technological Resurrection.Alexey Turchin - manuscript
    Abstract: In the future, it will be possible to create advance simulations of ancestor in computers. Superintelligent AI could make these simulations very similar to the real past by creating a simulation of all of humanity. Such a simulation would use all available data about the past, including internet archives, DNA samples, advanced nanotech-based archeology, human memories, as well as text, photos and videos. This means that currently living people will be recreated in such a simulation, and in (...)
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  16. Tools or Toys? On Specific Challenges for Modeling and the Epistemology of Models and Computer Simulations in the Social Sciences.Eckhart Arnold - manuscript
    Mathematical models are a well established tool in most natural sciences. Although models have been neglected by the philosophy of science for a long time, their epistemological status as a link between theory and reality is now fairly well understood. However, regarding the epistemological status of mathematical models in the social sciences, there still exists a considerable unclarity. In my paper I argue that this results from specific challenges that mathematical models and especially computer simulations face in the (...)
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  17. Content Aggregation, Visualization and Emergent Properties in Computer Simulations.Gordana Dodig-Crnkovic, Juan M. Durán & D. Slutej - 2010 - In Kai-Mikael Jää-Aro & Thomas Larsson (eds.), SIGRAD 2010 – Content aggregation and visualization. Linköping University Electronic Press. pp. 77-83.
    With the rapidly growing amounts of information, visualization is becoming increasingly important, as it allows users to easily explore and understand large amounts of information. However the field of information visualiza- tion currently lacks sufficient theoretical foundations. This article addresses foundational questions connecting information visualization with computing and philosophy studies. The idea of multiscale information granula- tion is described based on two fundamental concepts: information (structure) and computation (process). A new information processing paradigm of Granular Computing enables stepwise increase of (...)
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  18. How Models Fail. A Critical Look at the History of Computer Simulations of the Evolution of Cooperation.Catrin Misselhorn (ed.) - 2015 - Springer.
    Simulation models of the Reiterated Prisoner's Dilemma have been popular for studying the evolution of cooperation since more than 30 years now. However, there have been practically no successful instances of empirical application of any of these models. At the same time this lack of empirical testing and confirmation has almost entirely been ignored by the modelers community. In this paper, I examine some of the typical narratives and standard arguments with which these models are justified by their authors despite (...)
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  19. 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 (...)
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  20. How Simulations Fail.Patrick Grim, Robert Rosenberger, Adam Rosenfeld, Brian Anderson & Robb E. Eason - 2013 - 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 (...)
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  21. Les simulations computationnelles dans les sciences sociales.Franck Varenne - 2010 - Nouvelles Perspectives En Sciences Sociales 5 (2):17-49.
    Since the 1990’s, social sciences are living their computational turn. This paper aims to clarify the epistemological meaning of this turn. To do this, we have to discriminate between different epistemic functions of computation among the diverse uses of computers for modeling and simulating in the social sciences. Because of the introduction of a new – and often more user-friendly – way of formalizing and computing, the question of realism of formalisms and of proof value of computational treatments reemerges. Facing (...)
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  22.  31
    Explaining Altruism: A Simulation-Based Approach and its Limits.Eckhart Arnold - 2008 - Ontos Verlag.
    Employing computer simulations for the study of the evolution of altruism has been popular since Axelrod's book "The Evolution of Cooperation". But have the myriads of simulation studies that followed in Axelrod's footsteps really increased our knowledge about the evolution of altruism or cooperation? This book examines in detail the working mechanisms of simulation based evolutionary explanations of altruism. It shows that the "theoretical insights" that can be derived from simulation studies are often quite arbitrary and of little (...)
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  23. 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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  24. Transparency in Complex Computational Systems.Kathleen A. Creel - 2020 - Philosophy of Science 87 (4):568-589.
    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 s...
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  25. Is Simulation a Substitute for Experimentation?Isabelle Peschard - manuscript
    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 (in astrophysics, ecology, economics, climatology, etc.). 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 (...)
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  26. 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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  27.  49
    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 (...)
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  28.  69
    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 (...)
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  29. On Testing the Simulation Theory.Tom Campbell, Houman Owhadi, Joe Savageau & David Watkinson - manuscript
    Can the theory that reality is a simulation be tested? We investigate this question based on the assumption that if the system performing the simulation is nite (i.e. has limited resources), then to achieve low computational complexity, such a system would, as in a video game, render content (reality) only at the moment that information becomes available for observation by a player and not at the moment of detection by a machine (that would be part of the simulation and whose (...)
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  30. Innocence Lost: Simulation Scenarios: Prospects and Consequences.Barry Francis Dainton - manuscript
    Those who believe suitably programmed computers could enjoy conscious experience of the sort we enjoy must accept the possibility that their own experience is being generated as part of a computerized simulation. It would be a mistake to dismiss this is just one more radical sceptical possibility: for as Bostrom has recently noted, if advances in computer technology were to continue at close to present rates, there would be a strong probability that we are each living in a (...) simulation. The first part of this paper is devoted to broadening the scope of the argument: even if computers cannot sustain consciousness (as many dualists and materialists believe), there may still be a strong likelihood that we are living simulated lives. The implications of this result are the focus of the second part of the paper. The topics discussed include: the Doomsday argument, scepticism, the different modes of virtual life, transcendental idealism, the Problem of Evil, and simulation ethics. (shrink)
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  31. The Logic of the Method of Agent-Based Simulation in the Social Sciences: Empirical and Intentional Adequacy of Computer Programs.Nuno David, Jaime Sichman & Helder Coleho - 2005 - Journal of Artificial Societies and Social Simulation 8 (4).
    The classical theory of computation does not represent an adequate model of reality for simulation in the social sciences. The aim of this paper is to construct a methodological perspective that is able to conciliate the formal and empirical logic of program verification in computer science, with the interpretative and multiparadigmatic logic of the social sciences. We attempt to evaluate whether social simulation implies an additional perspective about the way one can understand the concepts of program and computation. We (...)
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  32.  26
    Simulating Grice: Emergent Pragmatics in Spatialized Game Theory.Patrick Grim - 2011 - In Anton Benz, Christian Ebert & Robert van Rooij (eds.), Language, Games, and Evolution. Springer-Verlag.
    How do conventions of communication emerge? How do sounds or gestures take on a semantic meaning, and how do pragmatic conventions emerge regarding the passing of adequate, reliable, and relevant information? My colleagues and I have attempted in earlier work to extend spatialized game theory to questions of semantics. Agent-based simulations indicate that simple signaling systems emerge fairly naturally on the basis of individual information maximization in environments of wandering food sources and predators. Simple signaling emerges by means of (...)
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  33. The Peer-to-Peer Simulation Hypothesis and a New Theory of Free Will.Marcus Arvan - 2015 - Scientia Salon.
    An overview of my work arguing that peer-to-peer computer networking (the Peer-to-Peer Simulation Hypothesis) may be the best explanation of quantum phenomena and a number of perennial philosophical problems.
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  34.  44
    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 (...)
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  35. What’s Wrong with Social Simulations?Eckhart Arnold - 2014 - The Monist 97 (3):359-377.
    This paper tries to answer the question why the epistemic value of so many social simulations is questionable. I consider the epistemic value of a social simulation as questionable if it contributes neither directly nor indirectly to the understanding of empirical reality. To examine this question, two classical social simulations are analyzed with respect to their possible epistemic justification: Schelling’s neighborhood segregation model and Axelrod’s reiterated Prisoner’s Dilemma simulations of the evolution of cooperation. It is argued that (...)
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  36.  72
    Is the Simulation Theory of Memory About Simulation?Nikola Andonovski - 2019 - Voluntas: Revista Internacional de Filosofia 10 (3):37.
    This essay investigates the notion of simulation and the role it plays in Kourken Michaelian's simulation theory of memory. I argue that the notion is importantly ambiguous and that this ambiguity may threaten some of the central commitments of the theory. To illustrate that, I examine two different conceptions of simulation: a narrow one (simulation as replication) and a broad one (simulation as computational modeling), arguing that the preferred narrow conception is incompatible with the claim that remembering involves the simulation (...)
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  37.  63
    Computing, Modelling, and Scientific Practice: Foundational Analyses and Limitations.Philippos Papayannopoulos - 2018 - Dissertation,
    This dissertation examines aspects of the interplay between computing and scientific practice. The appropriate foundational framework for such an endeavour is rather real computability than the classical computability theory. This is so because physical sciences, engineering, and applied mathematics mostly employ functions defined in continuous domains. But, contrary to the case of computation over natural numbers, there is no universally accepted framework for real computation; rather, there are two incompatible approaches --computable analysis and BSS model--, both claiming to formalise algorithmic (...)
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  38.  47
    What Kind of Science is Simulation?Patrick Grim - 2007 - Journal for Experimental and Theoretical Artificial Intelligence 19:19-28.
    Is simulation some new kind of science? We argue that instead simulation fits smoothly into existing scientific practice, but does so in several importantly different ways. Simulations in general, and computer simulations in particular, ought to be understood as techniques which, like many scientific techniques, can be employed in the service of various and diverse epistemic goals. We focus our attentions on the way in which simulations can function as (i) explanatory and (ii) predictive tools. We (...)
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  39. A Unified Explanation of Quantum Phenomena? The Case for the Peer‐to‐Peer Simulation Hypothesis as an Interdisciplinary Research Program.Marcus Arvan - 2014 - Philosophical Forum 45 (4):433-446.
    In my 2013 article, “A New Theory of Free Will”, I argued that several serious hypotheses in philosophy and modern physics jointly entail that our reality is structurally identical to a peer-to-peer (P2P) networked computer simulation. The present paper outlines how quantum phenomena emerge naturally from the computational structure of a P2P simulation. §1 explains the P2P Hypothesis. §2 then sketches how the structure of any P2P simulation realizes quantum superposition and wave-function collapse (§2.1.), quantum indeterminacy (§2.2.), wave-particle duality (...)
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  40. Computing Nature.Gordana Dodig-Crncovic & Raffaela Giovagnoli - 2013 - Springer.
    The articles in this volume present a selection of works from the Symposium on Natu-ral/Unconventional Computing at AISB/IACAP (British Society for the Study of Artificial Intelligence and the Simulation of Behaviour and The International Association for Computing and Philosophy) World Congress 2012, held at the University of Birmingham, celebrating Turing centenary. This book is about nature considered as the totality of physical existence, the universe. By physical we mean all phenomena - objects and processes - that are possible to detect (...)
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  41. Computer Models and the Evidence of Anthropogenic Climate Change: An Epistemology of Variety-of-Evidence Inferences and Robustness Analysis.Martin Vezer - 2016 - Computer Models and the Evidence of Anthropogenic Climate Change: An Epistemology of Variety-of-Evidence Inferences and Robustness Analysis MA Vezér Studies in History and Philosophy of Science 56:95-102.
    To study climate change, scientists employ computer models, which approximate target systems with various levels of skill. Given the imperfection of climate models, how do scientists use simulations to generate knowledge about the causes of observed climate change? Addressing a similar question in the context of biological modelling, Levins (1966) proposed an account grounded in robustness analysis. Recent philosophical discussions dispute the confirmatory power of robustness, raising the question of how the results of computer modelling studies contribute (...)
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  42. Semiotic Systems, Computers, and the Mind: How Cognition Could Be Computing.William J. Rapaport - 2012 - International Journal of Signs and Semiotic Systems 2 (1):32-71.
    In this reply to James H. Fetzer’s “Minds and Machines: Limits to Simulations of Thought and Action”, I argue that computationalism should not be the view that (human) cognition is computation, but that it should be the view that cognition (simpliciter) is computable. It follows that computationalism can be true even if (human) cognition is not the result of computations in the brain. I also argue that, if semiotic systems are systems that interpret signs, then both humans and computers (...)
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  43. Explanatory Completeness and Idealization in Large Brain Simulations: A Mechanistic Perspective.Marcin Miłkowski - 2016 - Synthese 193 (5):1457-1478.
    The claim defended in the paper is that the mechanistic account of explanation can easily embrace idealization in big-scale brain simulations, and that only causally relevant detail should be present in explanatory models. The claim is illustrated with two methodologically different models: Blue Brain, used for particular simulations of the cortical column in hybrid models, and Eliasmith’s SPAUN model that is both biologically realistic and able to explain eight different tasks. By drawing on the mechanistic theory of computational (...)
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  44. Using Simulation in the Assessment of Voting Procedures: An Epistemic Instrumental Approach.Marc Jiménez Rolland, Julio César Macías-Ponce & Luis Fernando Martínez-Álvarez - forthcoming - Simulation: Transactions of the Society for Modeling and Simulation International:1-8.
    In this paper, we argue that computer simulations can provide valuable insights into the performance of voting methods on different collective decision problems. This could improve institutional design, even when there is no general theoretical result to support the optimality of a voting method. To support our claim, we first describe a decision problem that has not received much theoretical attention in the literature. We outline different voting methods to address that collective decision problem. Under certain criteria of (...)
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  45. Simulation informatique et pluriformalisation des objets composites.Franck Varenne - 2009 - Philosophia Scientiae 13 (1):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 to call 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 (...)
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  46. 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. (...)
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  47.  11
    Simulated Annealing with a Temperature Dependent Penalty Function.Julio Michael Stern - 1992 - ORSA Journal on Computing 4:311-319.
    We formulate the problem of permuting a matrix to block angular form as the combinatorial minimization of an objective function. We motivate the use of simulated annealing (SA) as an optimization tool. We then introduce a heuristic temperature dependent penalty function in the simulated annealing cost function, to be used instead of the real objective function being minimized. Finally we show that this temperature dependent penalty function version of simulated annealing consistently outperforms the standard simulated annealing approach, producing, with smaller (...)
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  48.  9
    Models, Parameterization, and Software: Epistemic Opacity in Computational Chemistry.Frédéric Wieber & Alexandre Hocquet - 2020 - Perspectives on Science 28 (5):610-629.
    Computational chemistry grew in a new era of “desktop modeling,” which coincided with a growing demand for modeling software, especially from the pharmaceutical industry. Parameterization of models in computational chemistry is an arduous enterprise, and we argue that this activity leads, in this specific context, to tensions among scientists regarding the epistemic opacity transparency of parameterized methods and the software implementing them. We relate one flame war from the Computational Chemistry mailing List in order to assess in detail the relationships (...)
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  49. Simulation as Formal and Generative Social Science: The Very Idea.Nuno David, Jaime Sichman & Helder Coelho - 2007 - In Carlos Gershenson, Diederik Aerts & Bruce Edmonds (eds.), Worldviews, Science, and Us: Philosophy and Complexity. World Scientific. pp. 266--275.
    The formal and empirical-generative perspectives of computation are demonstrated to be inadequate to secure the goals of simulation in the social sciences. Simulation does not resemble formal demonstrations or generative mechanisms that deductively explain how certain models are sufficient to generate emergent macrostructures of interest. The description of scientific practice implies additional epistemic conceptions of scientific knowledge. Three kinds of knowledge that account for a comprehensive description of the discipline were identified: formal, empirical and intentional knowledge. The use of formal (...)
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  50. How Common Standards Can Diminish Collective Intelligence: A Computational Study.Michael Morreau & Aidan Lyon - 2016 - Journal of Evaluation in Clinical Practice 22 (4):483-489.
    Making good decisions depends on having accurate information – quickly, and in a form in which it can be readily communicated and acted upon. Two features of medical practice can help: deliberation in groups and the use of scores and grades in evaluation. We study the contributions of these features using a multi-agent computer simulation of groups of physicians. One might expect individual differences in members’ grading standards to reduce the capacity of the group to discover the facts on (...)
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