Results for 'Simulations of Science'

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  1. What Kind of Science is Simulation?Robb Eason, Robert Rosenberger, Trina Kokalis, Evan Selinger & 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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  2. 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 (...)
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  3. 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 (...)
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  4. Implications of computer science theory for the simulation hypothesis.David Wolpert - manuscript
    The simulation hypothesis has recently excited renewed interest, especially in the physics and philosophy communities. However, the hypothesis specifically concerns {computers} that simulate physical universes, which means that to properly investigate it we need to couple computer science theory with physics. Here I do this by exploiting the physical Church-Turing thesis. This allows me to introduce a preliminary investigation of some of the computer science theoretic aspects of the simulation hypothesis. In particular, building on Kleene's second recursion theorem, (...)
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  5. Implications of computer science theory for the simulation hypothesis.David Wolpert - manuscript
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  6. Philosophy of Science: A User's Guide.Adrian Currie & Sophie Veigl (eds.) - forthcoming - MIT Press.
    Thought experiments play a role in science and in some central parts of contemporary philosophy. They used to play a larger role in philosophy of science, but have been largely abandoned as part of the field’s “practice turn”. This chapter discusses possible roles for thought experimentation within a practice-oriented philosophy of science. Some of these roles are uncontroversial, such as exemplification and aiding discovery. A more controversial role is the reliance on thought experiments to justify philosophical claims. (...)
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  7. 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 by examining (...)
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  8. Agent-Based Models and Simulations in Economics and Social Sciences: from conceptual exploration to distinct ways of experimenting.Franck Varenne & Denis Phan - 2008 - In Nuno David, José Castro Caldas & Helder Coelho (eds.), Proceedings of the 3rd EPOS congress (Epistemological Perspectives On Simulations). pp. 51-69.
    Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological tools so as to show to what precise extent each author is right when he focuses on some empirical, instrumental or conceptual significance of his model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity, (...)
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  9. 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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  10. 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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  11. 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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  12. Simulation, self-extinction, and philosophy in the service of human civilization.Jeffrey White - 2016 - AI and Society 31 (2):171-190.
    Nick Bostrom’s recently patched ‘‘simulation argument’’ (Bostrom in Philos Q 53:243–255, 2003; Bos- trom and Kulczycki in Analysis 71:54–61, 2011) purports to demonstrate the probability that we ‘‘live’’ now in an ‘‘ancestor simulation’’—that is as a simulation of a period prior to that in which a civilization more advanced than our own—‘‘post-human’’—becomes able to simulate such a state of affairs as ours. As such simulations under consid- eration resemble ‘‘brains in vats’’ (BIVs) and may appear open to similar objections, (...)
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  13. 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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  14. The Termination Risks of Simulation Science.Preston Greene - 2020 - Erkenntnis 85 (2):489-509.
    Historically, the hypothesis that our world is a computer simulation has struck many as just another improbable-but-possible “skeptical hypothesis” about the nature of reality. Recently, however, the simulation hypothesis has received significant attention from philosophers, physicists, and the popular press. This is due to the discovery of an epistemic dependency: If we believe that our civilization will one day run many simulations concerning its ancestry, then we should believe that we are probably in an ancestor simulation right now. This (...)
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  15. 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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  16. 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 (...)
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  17. Framework for Models and Simulations with Agents in regard to Agent Simulations in Social Sciences: Emulation and Simulation.Franck Varenne - 2010 - In Alexandre Muzy, David R. C. Hill & Bernard P. Zeigler (eds.), Activity-Based Modeling and Simulation. Presses Universitaires Blaise-Pascal.
    The aim of this paper is to discuss the “Framework for M&S with Agents” (FMSA) proposed by Zeigler et al. [2000, 2009] in regard to the diverse epistemological aims of agent simulations in social sciences. We first show that there surely are great similitudes, hence that the aim to emulate a universal “automated modeler agent” opens new ways of interactions between these two domains of M&S with agents. E.g., it can be shown that the multi-level conception at the core (...)
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  18.  57
    In Vitro Analogies: Simulation Modeling in Bioengineering Sciences.Nancy Nersessian - forthcoming - In Tarja Knuuttila, Natalia Carrillo & Rami Koskinen (eds.), Routledge Handbook of Scientific Modeling. Routledge.
    This chapter focuses on a novel class of models used in frontier research in the bioengineering sciences – in vitro simulation models – that provide the basis for biological experimentation. These bioengineered models are hybrid constructions, composed of living tissues or cells and engineered materials. Specifically, it discusses the processes through which in vitro models were built, experimented with, and justified in a tissue engineering lab. It examines processes of design, construction, experimentation, evaluation, and redesign of in vitro simulation models, (...)
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  19. Science Transformed?: Debating Claims of an Epochal Break.Alfred Nordmann, Hans Radder & Gregor Schiemann (eds.) - 2011 - University of Pittsburgh Press.
    Advancements in computing, instrumentation, robotics, digital imaging, and simulation modeling have changed science into a technology-driven institution. Government, industry, and society increasingly exert their influence over science, raising questions of values and objectivity. These and other profound changes have led many to speculate that we are in the midst of an epochal break in scientific history. -/- This edited volume presents an in-depth examination of these issues from philosophical, historical, social, and cultural perspectives. It offers arguments both for (...)
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  20. 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 (§2.3.), (...)
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  21. Refounding of the activity concept? Towards a federative paradigm for modeling and simulation.Alexandre Muzy, Franck Varenne, Bernard P. Zeigler, Jonathan Caux, Patrick Coquillard, Luc Touraille, Dominique Prunetti, Philippe Caillou, Olivier Michel & David R. C. Hill - 2013 - Simulation - Transactions of the Society for Modeling and Simulation International 89 (2):156-177.
    Currently, the widely used notion of activity is increasingly present in computer science. However, because this notion is used in specific contexts, it becomes vague. Here, the notion of activity is scrutinized in various contexts and, accordingly, put in perspective. It is discussed through four scientific disciplines: computer science, biology, economics, and epistemology. The definition of activity usually used in simulation is extended to new qualitative and quantitative definitions. In computer science, biology and economics disciplines, the new (...)
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  22. Through the Eyes of Mad Men: Simulation, Interaction, and Ethics.Mitchell Aboulafia - 2011 - European Journal of Pragmatism and American Philosophy (2):133-147.
    Traditionally pragmatists have been favorably disposed to improving our understanding of agency and ethics through the use of empirical research. In the last two decades simulation theory has been championed in certain cognitive science circles as a way of explaining how we attribute mental states and predict human behavior. Drawing on research in psychology and neuroscience, Alvin I. Goldman and Robert M. Gordon have not only used simulation theory to discuss how we “mindread”, but have suggested that the theory (...)
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  23. Bayesian models and simulations in cognitive science.Giuseppe Boccignone & Roberto Cordeschi - 2007 - Workshop Models and Simulations 2, Tillburg, NL.
    Bayesian models can be related to cognitive processes in a variety of ways that can be usefully understood in terms of Marr's distinction among three levels of explanation: computational, algorithmic and implementation. In this note, we discuss how an integrated probabilistic account of the different levels of explanation in cognitive science is resulting, at least for the current research practice, in a sort of unpredicted epistemological shift with respect to Marr's original proposal.
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  24. Models, Unification, and Simulations: Margaret C. Morrison (1954–2021).Brigitte Falkenburg & Stephan Hartmann - 2021 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 52 (1):25-33.
    The philosophy of science community mourns the loss of Margaret Catherine Morrison, who passed away on January 9, 2021, after a long battle with cancer. Margie, as she was known to all who knew her, was highly regarded for her influential contributions to the philosophy of science, particularly her studies of the role of models and simulations in the natural and social sciences. These contributions made her a world-leading philosopher of science, instrumental in shifting philosophers' attention (...)
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  25. Better than Best: Epistemic Landscapes and Diversity of Practice in Science.Jingyi Wu - forthcoming - Philosophy of Science.
    When solving a complex problem in a group, should group members always choose the best available solution that they are aware of? In this paper, I build simulation models to show that, perhaps surprisingly, a group of agents who individually randomly follow a better available solution than their own can end up outperforming a group of agents who individually always follow the best available solution. This result has implications for the feminist philosophy of science and social epistemology.
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  26. 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 of simulation. (...)
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  27. Simulation and the We-Mode. A Cognitive Account of Plural First Persons.Matteo Bianchin - 2015 - Philosophy of the Social Sciences 45 (4-5):442-461.
    In this article, I argue that a capacity for mindreading conceived along the line of simulation theory provides the cognitive basis for forming we-centric representations of actions and goals. This explains the plural first personal stance displayed by we-intentions in terms of the underlying cognitive processes performed by individual minds, while preserving the idea that they cannot be analyzed in terms of individual intentional states. The implication for social ontology is that this makes sense of the plural subjectivity of joint (...)
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  28. Philosophy of Social Science in a nutshell: from discourse to model and experiment.Michel Dubois & Denis Phan - 2007 - In Denis Phan & Phan Amblard (eds.), Agent Based Modelling and Simulations in the Human and Social Siences. Oxford: The Bardwell Press. pp. 393-431.
    The debates on the scientificity of social sciences in general, and sociology in particular, are recurring. From the original methodenstreitat the end the 19th Century to the contemporary controversy on the legitimacy of “regional epistemologies”, a same set of interrogations reappears. Are social sciences really scientific? And if so, are they sciences like other sciences? How should we conceive “research programs” Lakatos (1978) or “research traditions” for Laudan (1977) able to produce advancement of knowledge in the field of social and (...)
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  29. 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 (...)
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  30. Theory, Simulation, and Neurological Similarity: Theory of Mind after 40 Years.Ali Yousefi Heris - 2018 - Eshare: An Iranian Journal of Philosophy 1 (2):12-38.
    One of the central problems in cognitive science concerns our ability to understand others in terms of mental state attribution. We, humans, think of each other as having minds, an assumption which indeed forms the basis of our daily communication: by attributing mental state we understand and predict each other’s behavior. But what mechanisms underpin this ability? This is a question that has preoccupied philosophers and cognitive scientists for more than four decades. In this paper, I will examine two (...)
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  31. Reflective and Evaluative Modes of Mental Simulation.Keith D. Markman & Matthew N. McMullen - 2005 - In David R. Mandel, Denis J. Hilton & Patrizia Catellani (eds.), The psychology of counterfactual thinking. New York: Routledge. pp. 77--93.
    A number of researchers have focused on the distinction between upward counterfactuals that simulate a better reality and downward counterfactuals that simulate a worse reality. In this chapter the authors will discuss the important aspects of a model (Markman and McMullen 2003) that attempts to explain how the very same counterfactual can engender dramatically different affective reactions. According to the model, the consequences of simulation direction are moderated by what we have termed simulation mode--relatively stronger tendencies to engage in reflective (...)
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  32. Could embodied simulation be a by-product of emotion perception?Edoardo Zamuner & Julian Kiverstein - 2010 - Behavioral and Brain Sciences 33 (6):449 - 449.
    The SIMS model claims that it is by means of an embodied simulation that we determine the meaning of an observed smile. This suggests that crucial interpretative work is done in the mapping that takes us from a perceived smile to the activation of one's own facial musculature. How is this mapping achieved? Might it depend upon a prior interpretation arrived at on the basis of perceptual and contextual information?
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  33. Doing Good with Virtual Reality: The Ethics of Using Virtual Simulations for Improving Human Morality.Jon Rueda - 2023 - In Andrew Kissel & Erick José Ramirez (eds.), Exploring Extended Realities: Metaphysical, Psychological, and Ethical Challenges. Routledge.
    Much of the excitement and concern with virtual reality (VR) has to do with the impact of virtual experiences on our moral conduct in the “real world”. VR technologies offer vivid simulations that may impact prosocial dispositions and abilities or emotions related to morality. Whereas some experiences could facilitate particular moral behaviors, VR could also inculcate bad moral habits or lead to the surreptitious development of nefarious moral traits. In this chapter, I offer an overview of the ethical debate (...)
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  34. Validation and Verification in Social Simulation: Patterns and Clarification of Terminology.Nuno David - 2009 - Epistemological Aspects of Computer Simulation in the Social Sciences, EPOS 2006, Revised Selected and Invited Papers, Lecture Notes in Artificial Intelligence, Squazzoni, Flaminio (Ed.) 5466:117-129.
    The terms ‘verification’ and ‘validation’ are widely used in science, both in the natural and the social sciences. They are extensively used in simulation, often associated with the need to evaluate models in different stages of the simulation development process. Frequently, terminological ambiguities arise when researchers conflate, along the simulation development process, the technical meanings of both terms with other meanings found in the philosophy of science and the social sciences. This article considers the problem of verification and (...)
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  35. On evolution of thinking about semiosis: semiotics meets cognitive science.Piotr Konderak - 2017 - Avant: Trends in Interdisciplinary Studies 7 (2):82-103.
    The aim of the paper is to sketch an idea—seen from the point of view of a cognitive scientist—of cognitive semiotics as a discipline. Consequently, the article presents aspects of the relationship between the two disciplines: semiotics and cognitive science. The main assumption of the argumentation is that at least some semiotic processes are also cognitive processes. At the methodological level, this claim allows for application of cognitive models as explanations of selected semiotic processes. In particular, the processes of (...)
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  36. Activating a Mental Simulation Mind-Set through Generation of Alternatives: Implications for Debiasing in Related and Unrelated Domains.Keith Markman, Edward Hirt & Frank Kardes - 2004 - Journal of Experimental Social Psychology 40 (3):374-383.
    Encouraging people to consider multiple alternatives appears to be a useful debiasing technique for reducing many biases (explanation, hindsight, and overconfidence), if the generation of alternatives is experienced as easy. The present research tests whether these alternative generation procedures induce a mental simulation mind-set (cf. Galinsky & Moskowitz, 2000), such that debiasing in one domain transfers to debias judgments in unrelated domains. The results indeed demonstrated that easy alternative generation tasks not only debiased judgments in the same domain but also (...)
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  37. Epistemology in a nutshell: Theory, model, simulation and Experiment.Denis Phan, Anne-Françoise Schmid & Franck Varenne - 2007 - In Denis Phan & Phan Amblard (eds.), Agent Based Modelling and Simulations in the Human and Social Siences. Oxford: The Bardwell Press. pp. 357-392.
    In the Western tradition, at least since the 14th century, the philosophy of knowledge has been built around the idea of knowledge as a representation [Boulnois 1999]. The question of the evaluation of knowledge refers at the same time (1) to the object represented (which one does one represent?), (2) to the process of knowledge formation, in particular with the role of the knowing subject (which one does one represent and how does one represent it?), and finally (3) to the (...)
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  38. Mirrors of the soul and mirrors of the brain? The expression of emotions as the subject of art and science.Machiel Keestra - 2014 - In Gary Schwartz (ed.), Emotions. Pain and pleasure in Dutch painting of the Golden Age. nai010 publishers. pp. 81-92.
    Is it not surprising that we look with so much pleasure and emotion at works of art that were made thousands of years ago? Works depicting people we do not know, people whose backgrounds are usually a mystery to us, who lived in a very different society and time and who, moreover, have been ‘frozen’ by the artist in a very deliberate pose. It was the Classical Greek philosopher Aristotle who observed in his Poetics that people could apparently be moved (...)
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  39. Ethical Issues with Simulating the Bridge Problem in VR.Erick Jose Ramirez & Scott LaBarge - 2020 - Science and Engineering Ethics 26 (6):3313-3331.
    We aim to generate a dilemma for virtual reality-based research that we motivate through an extended case study of Judith Thomson’s (1985) Bridge variant of the trolley problem. Though the problem we generate applies more broadly than the Bridge problem, we believe it makes a good exemplar of the kind of case we believe is problematic. First, we argue that simulations of these thought experiments run into a practicality horn that makes it practically impossible to produce them. These problems (...)
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  40. The search of “canonical” explanations for the cerebral cortex.Alessio Plebe - 2018 - History and Philosophy of the Life Sciences 40 (3):40.
    This paper addresses a fundamental line of research in neuroscience: the identification of a putative neural processing core of the cerebral cortex, often claimed to be “canonical”. This “canonical” core would be shared by the entire cortex, and would explain why it is so powerful and diversified in tasks and functions, yet so uniform in architecture. The purpose of this paper is to analyze the search for canonical explanations over the past 40 years, discussing the theoretical frameworks informing this research. (...)
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  41. 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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  42.  11
    Methodological Individualism and Agent-based Computational Simulation: A Reply to Kincaid and Zahle.Francesco Di Iorio - 2024 - Social Science Information.
    This study reflects on Harold Kincaid and Jule Zahle’s view that there is no necessary association between methodological individualism and agent-based models because the analysis of social phenomena in terms of the latter cannot always be regarded as an implementation of the former. Their view remains in contention with the standpoint of several philosophers of science and social scientists, including Chen and Di Iorio. Kincaid and Zahle’s main argument against such a standpoint is that agent-based simulation is compatible with (...)
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  43. From Silico to Vitro: Computational Models of Complex Biological Systems Reveal Real-World Emergent Phenomena.Orly Stettiner - 2016 - In Vincent C. Müller (ed.), Computing and philosophy: Selected papers from IACAP 2014. Cham: Springer. pp. 133-147.
    Computer simulations constitute a significant scientific tool for promoting scientific understanding of natural phenomena and dynamic processes. Substantial leaps in computational force and software engineering methodologies now allow the design and development of large-scale biological models, which – when combined with advanced graphics tools – may produce realistic biological scenarios, that reveal new scientific explanations and knowledge about real life phenomena. A state-of-the-art simulation system termed Reactive Animation (RA) will serve as a study case to examine the contemporary philosophical (...)
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  44. Incentives for Research Effort: An Evolutionary Model of Publication Markets with Double-Blind and Open Review.Mantas Radzvilas, Francesco De Pretis, William Peden, Daniele Tortoli & Barbara Osimani - 2023 - Computational Economics 61:1433-1476.
    Contemporary debates about scientific institutions and practice feature many proposed reforms. Most of these require increased efforts from scientists. But how do scientists’ incentives for effort interact? How can scientific institutions encourage scientists to invest effort in research? We explore these questions using a game-theoretic model of publication markets. We employ a base game between authors and reviewers, before assessing some of its tendencies by means of analysis and simulations. We compare how the effort expenditures of these groups interact (...)
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  45.  15
    From Silico to Vitro: Computational Models of Complex Biological Systems Reveal Real-World Emergent Phenomena.Orly Stettiner - 2016 - In Vincent C. Müller (ed.), Computing and philosophy: Selected papers from IACAP 2014. Cham: Springer. pp. 133-147.
    Computer simulations constitute a significant scientific tool for promoting scientific understanding of natural phenomena and dynamic processes. Substantial leaps in computational force and software engineering methodologies now allow the design and development of large-scale biological models, which – when combined with advanced graphics tools – may produce realistic biological scenarios, that reveal new scientific explanations and knowledge about real life phenomena. A state-of-the-art simulation system termed Reactive Animation (RA) will serve as a study case to examine the contemporary philosophical (...)
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  46. Computational Thought Experiments for a More Rigorous Philosophy and Science of the Mind.Iris Oved, Nikhil Krishnaswamy, James Pustejovsky & Joshua Hartshorne - 2024 - In L. K. Samuelson, S. L. Frank, M. Toneva, A. Mackey & E. Hazeltine (eds.), Proceedings of the 46th Annual Conference of the Cognitive Science Society. CC BY. pp. 601-609.
    We offer philosophical motivations for a method we call Virtual World Cognitive Science (VW CogSci), in which researchers use virtual embodied agents that are embedded in virtual worlds to explore questions in the field of Cognitive Science. We focus on questions about mental and linguistic representation and the ways that such computational modeling can add rigor to philosophical thought experiments, as well as the terminology used in the scientific study of such representations. We find that this method forces (...)
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  47.  33
    From Silico to Vitro: Computational Models of Complex Biological Systems Reveal Real-World Emergent Phenomena.Orly Stettiner - 2016 - In Vincent C. Müller (ed.), Computing and philosophy: Selected papers from IACAP 2014. Cham: Springer. pp. 133-147.
    Computer simulations constitute a significant scientific tool for promoting scientific understanding of natural phenomena and dynamic processes. Substantial leaps in computational force and software engineering methodologies now allow the design and development of large-scale biological models, which – when combined with advanced graphics tools – may produce realistic biological scenarios, that reveal new scientific explanations and knowledge about real life phenomena. A state-of-the-art simulation system termed Reactive Animation (RA) will serve as a study case to examine the contemporary philosophical (...)
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  48. Lightning in a Bottle: Complexity, Chaos, and Computation in Climate Science.Jon Lawhead - 2014 - Dissertation, Columbia University
    Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us better understand the (...)
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  49. Hacking the Simulation: From the Red Pill to the Red Team.Roman V. Yampolskiy - manuscript
    Many researchers have conjectured that the humankind is simulated along with the rest of the physical universe – a Simulation Hypothesis. In this paper, we do not evaluate evidence for or against such claim, but instead ask a computer science question, namely: Can we hack the simulation? More formally the question could be phrased as: Could generally intelligent agents placed in virtual environments find a way to jailbreak out of them. Given that the state-of-the-art literature on AI containment answers (...)
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  50. Cognitive Science: Recent Advances and Recurring Problems.Fred Adams, Joao Kogler & Osvaldo Pessoa Junior (eds.) - 2017 - Wilmington, DE, USA: Vernon Press.
    This book consists of an edited collection of original essays of the highest academic quality by seasoned experts in their fields of cognitive science. The essays are interdisciplinary, drawing from many of the fields known collectively as “the cognitive sciences.” Topics discussed represent a significant cross-section of the most current and interesting issues in cognitive science. Specific topics include matters regarding machine learning and cognitive architecture, the nature of cognitive content, the relationship of information to cognition, the role (...)
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